990 resultados para Extremely large maar volcanoes


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The rheological properties of dough and gluten are important for end-use quality of flour but there is a lack of knowledge of the relationships between fundamental and empirical tests and how they relate to flour composition and gluten quality. Dough and gluten from six breadmaking wheat qualities were subjected to a range of rheological tests. Fundamental (small-deformation) rheological characterizations (dynamic oscillatory shear and creep recovery) were performed on gluten to avoid the nonlinear influence of the starch component, whereas large deformation tests were conducted on both dough and gluten. A number of variables from the various curves were considered and subjected to a principal component analysis (PCA) to get an overview of relationships between the various variables. The first component represented variability in protein quality, associated with elasticity and tenacity in large deformation (large positive loadings for resistance to extension and initial slope of dough and gluten extension curves recorded by the SMS/Kieffer dough and gluten extensibility rig, and the tenacity and strain hardening index of dough measured by the Dobraszczyk/Roberts dough inflation system), the elastic character of the hydrated gluten proteins (large positive loading for elastic modulus [G'], large negative loadings for tan delta and steady state compliance [J(e)(0)]), the presence of high molecular weight glutenin subunits (HMW-GS) 5+10 vs. 2+12, and a size distribution of glutenin polymers shifted toward the high-end range. The second principal component was associated with flour protein content. Certain rheological data were influenced by protein content in addition to protein quality (area under dough extension curves and dough inflation curves [W]). The approach made it possible to bridge the gap between fundamental rheological properties, empirical measurements of physical properties, protein composition, and size distribution. The interpretation of this study gave indications of the molecular basis for differences in breadmaking performance.

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Three large deformation rheological tests, the Kieffer dough extensibility system, the D/R dough inflation system and the 2 g mixograph test, were carried out on doughs made from a large number of winter wheat lines and cultivars grown in Poland. These lines and cultivars represented a broad spread in baking performance in order to assess their suitability as predictors of baking volume. The parameters most closely associated with baking volume were strain hardening index, bubble failure strain, and mixograph bandwidth at 10min. Simple correlations with baking volume indicate that bubble failure strain and strain hardening index give the highest correlations, whilst the use of best subsets regression, which selects the best combination of parameters, gave increased correlations with R-2 = 0.865 for dough inflation parameters, R-2 = 0. 842 for Kieffer parameters and R-2 = 0.760 for mixograph parameters. (c) 2007 Elsevier Ltd. All rights reserved.

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Background The gut and immune system form a complex integrated structure that has evolved to provide effective digestion and defence against ingested toxins and pathogenic bacteria. However, great variation exists in what is considered normal healthy gut and immune function. Thus, whilst it is possible to measure many aspects of digestion and immunity, it is more difficult to interpret the benefits to individuals of variation within what is considered to be a normal range. Nevertheless, it is important to set standards for optimal function for use both by the consumer, industry and those concerned with the public health. The digestive tract is most frequently the object of functional and health claims and a large market already exists for gut-functional foods worldwide. Aim To define normal function of the gut and immune system and describe available methods of measuring it. Results We have defined normal bowel habit and transit time, identified their role as risk factors for disease and how they may be measured. Similarly, we have tried to define what is a healthy gut flora in terms of the dominant genera and their metabolism and listed the many, varied and novel methods for determining these parameters. It has proved less easy to provide boundaries for what constitutes optimal or improved gastric emptying, gut motility, nutrient and water absorption and the function of organs such as the liver, gallbladder and pancreas. The many tests of these functions are described. We have discussed gastrointestinal well being. Sensations arising from the gut can be both pleasant and unpleasant. However, the characteristics of well being are ill defined and merge imperceptibly from acceptable to unacceptable, a state that is subjective. Nevertheless, we feel this is an important area for future work and method development. The immune system is even more difficult to make quantitative judgements about. When it is defective, then clinical problems ensure, but this is an uncommon state. The innate and adaptive immune systems work synergistically together and comprise many cellular and humoral factors. The adaptive system is extremely sophisticated and between the two arms of immunity there is great redundancy, which provides robust defences. New aspects of immune function are discovered regularly. It is not clear whether immune function can be "improved". Measuring aspects of immune function is possible but there is no one test that will define either the status or functional capacity of the immune system. Human studies are often limited by the ability to sample only blood or secretions such as saliva but it should be remembered that only 2% of lymphocytes circulate at any given time, which limits interpretation of data. We recommend assessing the functional capacity of the immune system by: measuring specific cell functions ex vivo, measuring in vivo responses to challenge, e. g. change in antibody in blood or response to antigens, determining the incidence and severity of infection in target populations during naturally occurring episodes or in response to attenuated pathogens.

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Background: The large-scale production of G-protein coupled receptors (GPCRs) for functional and structural studies remains a challenge. Recent successes have been made in the expression of a range of GPCRs using Pichia pastoris as an expression host. P. pastoris has a number of advantages over other expression systems including ability to post-translationally modify expressed proteins, relative low cost for production and ability to grow to very high cell densities. Several previous studies have described the expression of GPCRs in P. pastoris using shaker flasks, which allow culturing of small volumes (500 ml) with moderate cell densities (OD600 similar to 15). The use of bioreactors, which allow straightforward culturing of large volumes, together with optimal control of growth parameters including pH and dissolved oxygen to maximise cell densities and expression of the target receptors, are an attractive alternative. The aim of this study was to compare the levels of expression of the human Adenosine 2A receptor (A(2A)R) in P. pastoris under control of a methanol-inducible promoter in both flask and bioreactor cultures. Results: Bioreactor cultures yielded an approximately five times increase in cell density (OD600 similar to 75) compared to flask cultures prior to induction and a doubling in functional expression level per mg of membrane protein, representing a significant optimisation. Furthermore, analysis of a C-terminally truncated A2AR, terminating at residue V334 yielded the highest levels (200 pmol/mg) so far reported for expression of this receptor in P. pastoris. This truncated form of the receptor was also revealed to be resistant to C-terminal degradation in contrast to the WT A(2A)R, and therefore more suitable for further functional and structural studies. Conclusion: Large-scale expression of the A(2A)R in P. pastoris bioreactor cultures results in significant increases in functional expression compared to traditional flask cultures.

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It is well understood that for haptic interaction: free motion performance and closed-loop constrained motion performance have conflicting requirements. The difficulties for both conditions are compounded when increased workspace is required as most solutions result in a reduction of achievable impedance and bandwidth. A method of chaining devices together to increase workspace without adverse effect on performance is described and analysed. The method is then applied to a prototype, colloquially known as 'The Flying Phantom', and shown to provide high-bandwidth, low impedance interaction over the full range of horizontal movement across the front of a human user.

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Large scientific applications are usually developed, tested and used by a group of geographically dispersed scientists. The problems associated with the remote development and data sharing could be tackled by using collaborative working environments. There are various tools and software to create collaborative working environments. Some software frameworks, currently available, use these tools and software to enable remote job submission and file transfer on top of existing grid infrastructures. However, for many large scientific applications, further efforts need to be put to prepare a framework which offers application-centric facilities. Unified Air Pollution Model (UNI-DEM), developed by Danish Environmental Research Institute, is an example of a large scientific application which is in a continuous development and experimenting process by different institutes in Europe. This paper intends to design a collaborative distributed computing environment for UNI-DEM in particular but the framework proposed may also fit to many large scientific applications as well.

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Many evolutionary algorithm applications involve either fitness functions with high time complexity or large dimensionality (hence very many fitness evaluations will typically be needed) or both. In such circumstances, there is a dire need to tune various features of the algorithm well so that performance and time savings are optimized. However, these are precisely the circumstances in which prior tuning is very costly in time and resources. There is hence a need for methods which enable fast prior tuning in such cases. We describe a candidate technique for this purpose, in which we model a landscape as a finite state machine, inferred from preliminary sampling runs. In prior algorithm-tuning trials, we can replace the 'real' landscape with the model, enabling extremely fast tuning, saving far more time than was required to infer the model. Preliminary results indicate much promise, though much work needs to be done to establish various aspects of the conditions under which it can be most beneficially used. A main limitation of the method as described here is a restriction to mutation-only algorithms, but there are various ways to address this and other limitations.