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Yield Analyses (yield + analysis)
Selected AbstractsAdjoint network method applied to the performance sensitivities of microwave amplifiersINTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, Issue 5 2006F. Güne Abstract This work focuses on the performance sensitivities of microwave amplifiers using the "adjoint network and adjoint variable" method, via "wave" approaches, which includes sensitivities of the transducer power gain, noise figure, and magnitudes and phases of the input and output reflection coefficients. The method can be extended to sensitivities of the other performance measure functions. The adjoint-variable methods for design-sensitivity analysis offer computational speed and accuracy. They can be used for efficiency-based gradient optimization, in tolerance and yield analyses. In this work, an arbitrarily configured microwave amplifier is considered: firstly, each element in the network is modeled by the scattering matrix formulation, then the topology of the network is taken into account using the connection scattering-matrix formulation. The wave approach is utilized in the evaluation of all the performance-measurement functions, then sensitivity invariants are formulated using Tellegen's theorem. Performance sensitivities of the T- and ,-types of distributed-parameter amplifiers are considered as a worked example. The numerical results of T- and ,-type amplifiers for the design targets of noise figure Freq = 0.46 dB , 1,12 and Vireq = 1, GTreq = 12 dB , 15.86 in the frequency range 2,11 GHz are given in comparison to each other. Furthermore, analytical methods of the "gain factorisation" and "chain sensitivity parameter" are applied to the gain and noise sensitivities as well. In addition, "numerical perturbation" is applied to calculation of all the sensitivities. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006. [source] Evaluating Tripsacum -introgressed maize germplasm after infestation with western corn rootworms (Coleoptera: Chrysomelidae)JOURNAL OF APPLIED ENTOMOLOGY, Issue 1 2009D. A. Prischmann Abstract Maize (Zea mays L.) is a valuable commodity throughout the world, but corn rootworms (Chrysomelidae: Diabrotica spp.) often cause economic damage and increase production costs. Current rootworm management strategies have limitations, and in order to create viable management alternatives, researchers have been developing novel maize lines using Eastern gamagrass (Tripsacum dactyloides L.) germplasm, a wild relative of maize that is resistant to rootworms. Ten maize Tripsacum -introgressed inbred lines derived from recurrent selection of crosses with gamagrass and teosinte (Zea diploperennis Iltis) recombinants and two public inbred lines were assessed for susceptibility to western corn rootworm (Diabrotica virgifera virgifera LeConte) and yield in a two-year field study. Two experimental maize inbred lines, SDG11 and SDG20, had mean root damage ratings that were significantly lower than the susceptible public line B73. Two other experimental maize inbred lines, SDG12 and SDG6, appeared tolerant to rootworm damage because they exhibited yield increases after rootworm infestation in both years. In the majority of cases, mean yield per plant of experimental maize lines used in yield analyses was equal to or exceeded that of the public inbred lines B73 and W64A. Our study indicates that there is potential to use Tripsacum -introgressed maize germplasm in breeding programs to enhance plant resistance and/or tolerance to corn rootworms, although further research on insect resistance and agronomic potential of this germplasm needs to be conducted in F1 hybrids. [source] Reduction of a set of elementary modes using yield analysisBIOTECHNOLOGY & BIOENGINEERING, Issue 2 2009Hyun-Seob Song Abstract This article proposes a new concept termed "yield analysis" (YA) as a method of extracting a subset of elementary modes (EMs) essential for describing metabolic behaviors. YA can be defined as the analysis of metabolic pathways in yield space where the solution space is a bounded convex hull. Two important issues arising in the analysis and modeling of a metabolic network are handled. First, from a practical sense, the minimal generating set spanning the yield space is recalculated. This refined generating set excludes all the trivial modes with negligible contribution to convex hull in yield space. Second, we revisit the problem of decomposing the measured fluxes among the EMs. A consistent way of choosing the unique, minimal active modes among a number of possible candidates is discussed and compared with two other existing methods, that is, those of Schwartz and Kanehisa (Schwartz and Kanehisa, 2005. Bioinformatics 21: 204,205) and of Provost et al. (Provost et al., 2007. Proceedings of the 10th IFAC Symposium on Computer Application in Biotechnology, 321,326). The proposed idea is tested in a case study of a metabolic network of recombinant yeasts fermenting both glucose and xylose. Due to the nature of the network with multiple substrates, the flux space is split into three independent yield spaces to each of which the two-staged reduction procedure is applied. Through a priori reduction without any experimental input, the 369 EMs in total was reduced to 35 modes, which correspond to about 91% reduction. Then, three and four modes were finally chosen among the reduced set as the smallest active sets for the cases with a single substrate of glucose and xylose, respectively. It should be noted that the refined minimal generating set obtained from a priori reduction still provides a practically complete description of all possible states in the subspace of yields, while the active set covers only a specific set of experimental data. Biotechnol. Bioeng. 2009;102: 554,568. © 2008 Wiley Periodicals, Inc. [source] | ||||||||||