941 resultados para Dynamic shelf
Resumo:
Uncatalyzed, ring-opening polymerization of individual macrocyclic poly(arylene thioether ketone)s (1-4) and mixtures (5) under dynamic heating conditions has been demonstrated for the first time. High-molecular-weight, film-forming products were obtained after heating of the macrocycles up to 480 degreesC, with a heating rate of 10-20 degreesC /min. Depending on the macrocyclic structure and heat treatment conditions, the polymers obtained were amorphous or semicrystalline, soluble or slightly crosslinked. NMR analyses of the soluble polymers revealed their linear, highly regular structure. According to NMR, DSC, and TGA studies, the polymers obtained do not contain any residual macrocycles. The polymers with thio-p-arylene moieties in the main chain were thermally stabile. The catalyzed ring opening polymerization of 5 carried out in diphenyl sulfone solution is also reported for comparison. Using quantum mechanical calculations of the ring opening of macrocycles, a reaction mechanism is suggested. Preparation of nanosized poly(thioether ketone) fibrils by a replication method is described.
Resumo:
This paper discusses experimental and theoretical investigations and Computational Fluid Dynamics (CFD) modelling considerations to evaluate the performance of a square section wind catcher system connected to the top of a test room for the purpose of natural ventilation. The magnitude and distribution of pressure coefficients (C-p) around a wind catcher and the air flow into the test room were analysed. The modelling results indicated that air was supplied into the test room through the wind catcher's quadrants with positive external pressure coefficients and extracted out of the test room through quadrants with negative pressure coefficients. The air flow achieved through the wind catcher depends on the speed and direction of the wind. The results obtained using the explicit and AIDA implicit calculation procedures and CFX code correlate relatively well with the experimental results at lower wind speeds and with wind incidents at an angle of 0 degrees. Variation in the C-p and air flow results were observed particularly with a wind direction of 45 degrees. The explicit and implicit calculation procedures were found to be quick and easy to use in obtaining results whereas the wind tunnel tests were more expensive in terms of effort, cost and time. CFD codes are developing rapidly and are widely available especially with the decreasing prices of computer hardware. However, results obtained using CFD codes must be considered with care, particularly in the absence of empirical data.
Resumo:
Strategy is a contested concept. The generic literature is characterized by a diverse range of competing theories and alternative perspectives. Traditional models of the competitive strategy of construction firms have tended to focus on exogenous factors. In contrast, the resource-based view of strategic management emphasizes the importance of endogenous factors. The more recently espoused concept of dynamic capabilities extends consideration beyond static resources to focus on the ability of firms to reconfigure their operating routines to enable responses to changing environments. The relevance of the dynamics capabilities framework to the construction sector is investigated through an exploratory case study of a regional contractor. The focus on how firms continuously adapt to changing environments provides new insights into competitive strategy in the construction sector. Strong support is found for the importance of path dependency in shaping strategic choice. The case study further suggests that strategy is a collective endeavour enacted by a loosely defined group of individual actors. Dynamic capabilities are characterized by an empirical elusiveness and as such are best construed as situated practices embedded within a social and physical context.
Resumo:
Developmental and biophysical leaf characteristics that influence post-harvest shelf life in lettuce, an important leafy crop, have been examined. The traits were studied using 60 informative F-9 recombinant inbed lines (RILs) derived from a cross between cultivated lettuce (Lactuca sativa cv. Salinas) and wild lettuce (L. serriola acc. UC96US23). Quantitative trait loci (QTLs) for shelf life co-located most closely with those for leaf biophysical properties such as plasticity, elasticity, and breakstrength, suggesting that these are appropriate targets for molecular breeding for improved shelf life. Significant correlations were found between shelf life and leaf size, leaf weight, leaf chlorophyll content, leaf stomatal index, and epidermal cell number per leaf, indicating that these pre-harvest leaf development traits confer post-harvest properties. By studying the population in two contrasting environments in northern and southern Europe, the genotype by environment interaction effects of the QTLs relevant to leaf development and shelf life were assessed. In total, 107 QTLs, distributed on all nine linkage groups, were detected from the 29 traits. Only five QTLs were common in both environments. Several areas where many QTLs co-located (hotspots) on the genome were identified, with relatively little overlap between developmental hotspots and those relating to shelf life. However, QTLs for leaf biophysical properties (breakstrength, plasticity, and elasticity) and cell area correlated well with shelf life, confirming that the ideal ideotype lettuce should have small cells with strong cell walls. The identification of QTLs for leaf development, strength, and longevity will lead to a better understanding of processability at a genetic and cellular level, and allow the improvement of salad leaf quality through marker-assisted breeding.
The dynamic development and distribution of gas cells in breadmaking dough during proving and baking
Resumo:
Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.
Resumo:
This paper investigates the use of really simple syndication (RSS) to dynamically change virtual environments. The case study presented here uses meteorological data downloaded from the Internet in the form of an RSS feed, this data is used to simulate current weather patterns in a virtual environment. The downloaded data is aggregated and interpreted in conjunction with a configuration file, used to associate relevant weather information to the rendering engine. The engine is able to animate a wide range of basic weather patterns. Virtual reality is a way of immersing a user into a different environment, the amount of immersion the user experiences is important. Collaborative virtual reality will benefit from this work by gaining a simple way to incorporate up-to-date RSS feed data into any environment scenario. Instead of simulating weather conditions in training scenarios, actual weather conditions can be incorporated, improving the scenario and immersion.
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Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.