Recent advances in image reconstruction, coil sensitivity calibration, and coil array design for SMASH and generalized parallel MRI.

Parallel magnetic resonance imaging (MRI) techniques use spatial information from arrays of radiofrequency (RF) detector coils to accelerate imaging. A number of parallel MRI techniques have been described in recent years, and numerous clinical applications are currently being explored. The advent of practical parallel imaging presents various challenges for image reconstruction and RF system design. Recent advances in tailored SiMultaneous Acquisition of Spatial Harmonics (SMASH) image reconstructions are summarized. These advances enable robust SMASH imaging in arbitrary image planes with a wide range of coil array geometries. A generalized formalism is described which may be used to understand the relations between SMASH and SENSE, to derive typical implementations of each as special cases, and to form hybrid techniques combining some of the advantages of both. Accurate knowledge of coil sensitivities is crucial for parallel MRI, and errors in calibration represent one of the most common and the most pernicious sources of error in parallel image reconstructions. As one example, motion of the patient and/or the coil array between the sensitivity reference scan and the accelerated acquisition can lead to calibration errors and reconstruction artifacts. Self-calibrating parallel MRI approaches that address this problem by eliminating the need for external sensitivity references are reviewed. The ultimate achievable signal-to-noise ratio (SNR) for parallel MRI studies is closely tied to the geometry and sensitivity patterns of the coil arrays used for spatial encoding. Several parallel imaging array designs that depart from the traditional model of overlapped adjacent loop elements are described.     

Solvent interactions with n ring systems in proteins

The interaction of water molecules with apolar amino acids isan important aspect of the hydrophobic effect and hence of proteinfolding. Our distributed multipole electrostatic model for waterinteracting with phenylalanine dipeptides shows that minimumenergy sites exist above the aromatic ring such that a solventmolecule can interact with the electrons, but only when thissite is not blocked by mainchain atoms or disturbed by main-chainpolar atoms. This is consistent with the experimental evidenceof others that water can hydrogen bond to aromatic n electrons.In contrast, our analysis of solvent interactions with phenylalanineresidues based on 48 high-resolution, well-refined protein structuresshows that the dominant interaction of solvent molecules iswith the edge of the ring and not with the 7i electrons. Asthe faces of phenylalanine rings tend to be buried, and solventinteractions with neighbouring polar atoms are more favourable,the interaction of water molecules with the faces of aromatic rings appears not to occur frequently in proteins     

A strategy for controlling charge and conformation in 2,2′-bipyridine complexes for use in photonic applications

The complex [ⁿBu₄N][Cu(H1)₂]·H₂O (H₂1 = 3,3′-dihydroxy-6,6′-dimethyl-2,2′-bipyridine) is readily formed from the reaction of H₂1 with [Cu(MeCN)₄][PF₆] in the presence of [ⁿBu₄N]Br; in the solid state the anion comprises a discrete dinuclear {[Cu(H1)₂](H₂O)₂[Cu(H1)₂]}^2– unit in which two oxygen atoms of each [H1]^– ligand and two water oxygens form a chair shaped hydrogen-bonded six-membered ring.     

Investigation of the impact of changes in demand forecasting method on the financial performance of an electricity supply undertaking

Peak demand forecasts obtained from six different univariate forecasting methods, under a range of conditions, were used to drive a capacity acquisition model of a large electrical supply system; and the resulting physical and financial performance of the model was observed for each set of forecasts. The results obtained are discussed in the context of their implications for the choice of load forecasting method used in capacity acquisition planning by a power supply undertaking.     

Information-Based Dynamic Manufacturing System Scheduling

Information about the state of the system is of paramount importance in determining the dynamics underlying manufacturing systems. In this paper, we present an adaptive scheduling policy for dynamic manufacturing system scheduling using information obtained from snapshots of the system at various points in time. Specifically, the framework presented allows for information-based dynamic scheduling where information collected about the system is used to (1) adjust appropriate parameters in the system and (2) search or optimize using genetic algorithms. The main feature of this policy is that it tailors the dispatching rule to be used at a given point in time to the prevailing state of the system. Experimental studies indicate the superiority of the suggested approach over the alternative approach involving the repeated application of a single dispatching rule for randomly generated test problems as well as a real system. In pa ticular, its relative performance improves further when there are frequent disruptions and when disruptions are caused by the introduction of tight due date jobs and machine breakdown—two of the most common sources of disruption in most manufacturing systems. From an operational perspective, the most important characteristics of the pattern-directed scheduling approach are its ability to incorporate the idiosyncratic characteristics of the given system into the dispatching rule selection process and its ability to refine itself incrementally on a continual basis by taking new system parameters into account.