164 resultados para sampled value process bus


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We demonstrate complete characterization of a two-qubit entangling process-a linear optics controlled-NOT gate operating with coincident detection-by quantum process tomography. We use a maximum-likelihood estimation to convert the experimental data into a physical process matrix. The process matrix allows an accurate prediction of the operation of the gate for arbitrary input states and a calculation of gate performance measures such as the average gate fidelity, average purity, and entangling capability of our gate, which are 0.90, 0.83, and 0.73, respectively.

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The acquisition and extinction of affective valence to neutral geometrical shape conditional stimuli was investigated in three experiments. Experiment 1 employed a differential conditioning procedure with aversive shock USs. Differential electrodermal responding was evident during acquisition and lost during extinction. As indexed by verbal ratings, the CS1 acquired negative valence during acquisition,which was reduced after extinction. Affective priming, a reaction time based demand free measure of stimulus valence, failed to provide evidence for affective learning. Experiment 2 employed pictures of happy and angry faces as USs.Valence ratings after acquisitionweremore positive for theCS paired with happy faces (CS-H) and less positive for the CS paired with angry faces (CS-A) than during baseline. Extinction training reduced the extent of acquired valence significantly for both CSs, however, ratings of the CS-A remained different from baseline. Affective priming confirmed these results yielding differences between CS-A and CS-H after acquisition for pleasant and unpleasant targets, but for pleasant targets only after extinction. Experiment 3 replicated the design of Experiment 2, but presented the US pictures backwardly masked. Neither rating nor affective priming measures yielded any evidence for affective learning. The present results confirm across two different experimental procedures that, contrary to predictions from dual process accounts of human learning, affective learning is subject to extinction.

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An efficient system is now in place for improving diverse sugarcane cultivars by genetic transformation, that is, the insertion of useful new genes into single cells followed by the regeneration of genetically modified (transgenic) plants. The method has already been used to introduce genes for resistance to several major diseases, insect pests and a herbicide, Field testing has begun, and research is underway to identify other genes for increased environmental stress resistance, agronomic efficiency and yield of sucrose or other valuable products. Experience in other crops has shown that genetically improved varieties which provide genuine environmental and consumer benefits are welcomed by producers and consumers. Substantial research is still needed, but these new gene technologies will reshape the sugar industry and determine the international competitive efficiency of producers.

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The value of a seasonal forecasting system based on phases of the Southern Oscillation was estimated for a representative dryland wheat grower in the vicinity of Goondiwindi. In particular the effects on this estimate of risk attitude and planting conditions were examined. A recursive stochastic programming approach was used to identify the grower's utility-maximising action set in the event of each of the climate patterns over the period 1894-1991 recurring In the imminent season. The approach was repeated with and without use of the forecasts. The choices examined were, at planting, nitrogen application rate and cultivar and, later in the season, choices of proceeding with or abandoning each wheat activity, The value of the forecasting system was estimated as the maximum amount the grower could afford to pay for its use without expected utility being lowered relative to its non use.

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An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

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The present study investigated the relationship between plasma potassium ion concentration ([K+]) and skeletal muscle torque during three different 15-min recovery periods after fatigue induced by four 30-s sprints. Four males and one female completed the multiple sprint exercise on three separate days; recovery was passive, i.e. no cycling exercise (PRec), active cycling at 30% peak oxygen consumption (V) over dot(2peak) (30% Rec) and active cycling at 60% (V) over dot(2peak) (60% Rec). Plasma [K+] was measured from blood sampled from an antecubital vein of subjects at rest and at 0, 3, 5, 10 and 15 min into each recovery. Isokinetic leg strength was measured at rest and at 1, 6, 11 and 16 min during each recovery. Following the exhaustive sprints; [K+] increased significantly from an average mean (SEM) resting value of 3.81 (0.07) mmol.l(-1) to 4.48 (0.19) mmol.l(-1) (P < 0.01). In all recovery conditions, plasma [K+] returned to resting levels within 3 min following the fourth sprint. However, in the two active recovery conditions plasma [K+] increased over the remainder of the recovery periods to 4.36 (0.12) mmol.l(-1) in the 30% Rec condition and 4.62 (0.12) mmol.l(-1) in the 60% Rec condition, the latter being significantly higher than the former (P < 0.01). The maximum torque measured following the sprints decreased significantly, on average, to 61.1 (8.36)% of peak levels (P < 0.01). After 15 min of recovery, maximum torque was highest in the 30% Rec condition at 92.13 (3.06)% of peak levels (P < 0.01), compared to 85.23 (3.64)% and 85.71 (0.82)% for the PRec and 60% Rec conditions, respectively. In contrast to the significant differences in plasma [K+] across all three recovery conditions, muscle torque recovery was significantly different in only the 30% Rec condition. In summary, recovery of peak levels of muscle torque following fatiguing exercise does not appear to follow changes in plasma [K+].

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In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

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A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

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Chinese-style dried, shredded meat is traditionally prepared by sequential cooking, shredding, pre-drying, and final drying (roasting) of lean meat. In this study, shredded dried beef (a(w)<0.6) was prepared by omitting roasting but prolonging pre-drying. Sensory scores of the modified product were lower than those for the traditional product. When heat pump drying replaced traditional oven drying, drying time was shortened without significant difference in quality attributes. Desorption curves were established for shredded beef at several drying temperatures.