No description available.

No description available.

No description available.

Wheat canopies were grown at either 330 or 1200 μmol mol-1 CO2 in sealed controlled environments, where carbon fluxes and radiation interception were continuously and nondestructively measured during their life cycles. The effects of elevated CO2 on daily growth rates, canopy quantum yield, canopy and root carbon use efficiencies, and final dry mass were calculated from carbon flux measurements in an open gas exchange system. Dry biomass at harvest was predicted from the gas exchange data to within ± 8%. The greatest effect of elevated CO2 occurred in the first 15d after emergence; however, several physiological processes were enhanced throughout the life cycle. Elevated CO2 increased average net photosynthesis by 30%, average shoot respiration by 10%, and average root respiration by 40%. Crop growth rate, calculated from gas exchange data, was 30% higher during both vegetative growth and reproductive growth. Elevated CO 2 did not affect radiation interception, but increased average canopy quantum yield from 0.039 to 0.051 (31%). Average canopy carbon use efficiency was increased by 12%. Although harvest index was unaffected, these increases in the physiological determinants of yield by elevated CO2 resulted in a 14% increase in seed yield.

There is no doubt that computerized tomography (CT) is highly beneficial for patients when used appropriately for diagnostic purposes. However, worries have been raised concerning the possible risk of cancer induction from CT because of the dramatic increase of CT usage in medicine. It is crucial to keep the radiation dose as low as reasonably achievable to reduce this probable risk. This thesis is about to reduce X-ray radiation exposure to patients and/or CT operators via a new imaging modality that exploits the recent compressed sensing (CS) theory. Two efficient reconstruction algorithms based on total variation (TV) minimization of estimated images are proposed. Using fewer measurements than the traditional filtered back projection based algorithms or algebraic reconstruction techniques require, the proposed algorithms allow reducing the radiation dose without sacrificing the CT image quality even in the case of noisy measurements. Employing powerful methods to solve the TV minimization problem, both schemes have higher reconstruction speed than the recently introduced CS based algorithms.