5 resultados para loss allocation

em CaltechTHESIS


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The technique of variable-angle, electron energy-loss spectroscopy has been used to study the electronic spectroscopy of the diketene molecule. The experiment was performed using incident electron beam energies of 25 eV and 50 eV, and at scattering angles between 10° and 90°. The energy-loss region from 2 eV to 11 eV was examined. One spin-forbidden transition has been observed at 4.36 eV and three others that are spin-allowed have been located at 5.89 eV, 6.88 eV and 7.84 eV. Based on the intensity variation of these transitions with impact energy and scattering angle, and through analogy with simpler molecules, the first three transitions are tentatively assigned to an n → π* transition, a π - σ* (3s) Rydberg transition and a π → π* transition.

Thermal decomposition of chlorodifluoromethane, chloroform, dichloromethane and chloromethane under flash-vacuum pyrolysis conditions (900-1100°C) was investigated by the technique of electron energy-loss spectroscopy, using the impact energy of 50 eV and a scattering angle of 10°. The pyrolytic reaction follows a hydrogen-chloride α-elimination pathway. The difluoromethylene radical was produced from chlorodifluoromethane pyrolysis at 900°C and identified by its X^1 A_1 → A^1B_1 band at 5.04 eV.

Finally, a number of exploratory studies have been performed. The thermal decomposition of diketene was studied under flash vacuum pressures (1-10 mTorr) and temperatures ranging from 500°C to 1000°C. The complete decomposition of the diketene molecule into two ketene molecules was achieved at 900°C. The pyrolysis of trifluoromethyl iodide molecule at 1000°C produced an electron energy-loss spectrum with several iodine-atom, sharp peaks and only a small shoulder at 8.37 eV as a possible trifluoromethyl radical feature. The electron energy-loss spectrum of trichlorobromomethane at 900°C mainly showed features from bromine atom, chlorine molecule and tetrachloroethylene. Hexachloroacetone decomposed partially at 900°C, but showed well-defined features from chlorine, carbon monoxide and tetrachloroethylene molecules. Bromodichloromethane molecule was investigated at 1000°C and produced a congested, electron energy-loss spectrum with bromine-atom, hydrogen-bromide, hydrogen-chloride and tetrachloroethylene features.

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Mitochondria can remodel their membranes by fusing or dividing. These processes are required for the proper development and viability of multicellular organisms. At the cellular level, fusion is important for mitochondrial Ca2+ homeostasis, mitochondrial DNA maintenance, mitochondrial membrane potential, and respiration. Mitochondrial division, which is better known as fission, is important for apoptosis, mitophagy, and for the proper allocation of mitochondria to daughter cells during cellular division.

The functions of proteins involved in fission have been best characterized in the yeast model organism Sarccharomyces cerevisiae. Mitochondrial fission in mammals has some similarities. In both systems, a cytosolic dynamin-like protein, called Dnm1 in yeast and Drp1 in mammals, must be recruited to the mitochondrial surface and polymerized to promote membrane division. Recruitment of yeast Dnm1 requires only one mitochondrial outer membrane protein, named Fis1. Fis1 is conserved in mammals, but its importance for Drp1 recruitment is minor. In mammals, three other receptor proteins—Mff, MiD49, and MiD51—play a major role in recruiting Drp1 to mitochondria. Why mammals require three additional receptors, and whether they function together or separately, are fundamental questions for understanding the mechanism of mitochondrial fission in mammals.

We have determined that Mff, MiD49, or MiD51 can function independently of one another to recruit Drp1 to mitochondria. Fis1 plays a minor role in Drp1 recruitment, suggesting that the emergence of these additional receptors has replaced the system used by yeast. Additionally, we found that Fis1/Mff and the MiDs regulate Drp1 activity differentially. Fis1 and Mff promote constitutive mitochondrial fission, whereas the MiDs activate recruited Drp1 only during loss of respiration.

To better understand the function of the MiDs, we have determined the atomic structure of the cytoplasmic domain of MiD51, and performed a structure-function analysis of MiD49 based on its homology to MiD51. MiD51 adopts a nucleotidyl transferase fold, and binds ADP as a co-factor that is essential for its function. Both MiDs contain a loop segment that is not present in other nucleotidyl transferase proteins, and this loop is used to interact with Drp1 and to recruit it to mitochondria.

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This thesis brings together four papers on optimal resource allocation under uncertainty with capacity constraints. The first is an extension of the Arrow-Debreu contingent claim model to a good subject to supply uncertainty for which delivery capacity has to be chosen before the uncertainty is resolved. The second compares an ex-ante contingent claims market to a dynamic market in which capacity is chosen ex-ante and output and consumption decisions are made ex-post. The third extends the analysis to a storable good subject to random supply. Finally, the fourth examines optimal allocation of water under an appropriative rights system.

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Real-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.

In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.

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Experimental measurements of rate of energy loss were made for protons of energy .5 to 1.6 MeV channeling through 1 μm thick silicon targets along the <110>, <111>, and <211> axial directions, and the {100}, {110}, {111}, and {211} planar directions. A .05% resolution automatically controlled magnetic spectrometer was used. The data are presented graphically along with an extensive summary of data in the literature. The data taken cover a wider range of channels than has previously been examined, and are in agreement with the data of F. Eisen, et al., Radd. Eff. 13, 93 (1972).

The theory in the literature for channeling energy loss due to interaction with local electrons, core electrons, and distant valence electrons of the crystal atoms is summarized. Straggling is analyzed, and a computer program which calculates energy loss and straggling using this theory and the Moliere approximation to the Thomas Fermi potential, VTF, and the detailed silicon crystal structure is described. Values for the local electron density Zloc in each of the channels listed above are extracted from the data by graphical matching of the experimental and computer results.

Zeroth and second order contributions to Zloc as a function of distance from the center of the channel were computed from ∇2VTF = 4πρ for various channels in silicon. For data taken in this work and data of F. Eisen, et al., Rad. Eff. 13, 93 (1972), the calculated zeroth order contribution to Zloc lies between the experimentally extracted Zloc values obtained by using the peak and the leading edge of the transmission spectra, suggesting that the observed straggling is due both to statistical fluctuations and to path variation.