67 research outputs found

    Advances in Molecular Quantum Chemistry Contained in the Q-Chem 4 Program Package

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    A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller–Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube

    Infectious diseases in allogeneic haematopoietic stem cell transplantation: prevention and prophylaxis strategy guidelines 2016

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    Geographical miss during intracoronary irradiation: impact on restenosis and determination of required safety margin length

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    AbstractObjectivesThe goal of this study was to evaluate the incidence and effects of underdosage of injured segments during intracoronary irradiation and to define the minimal length of safety margin required to avoid mismatched source placement.BackgroundUnderdosage of injured segments due to misplacement of active source has been suggested as the underlying mechanism for the occurrence of edge restenosis.MethodsBaseline angiograms of 112 vessels in 109 patients with in-stent restenosis undergoing coronary reintervention followed by intracoronary irradiation (192Ir: Checkmate, Cordis, Miami, Florida; 32P: Gallileo, Guidant, Houston, Texas; 90Sr/Y: Beta-Cath, Novoste, Norcross, Georgia) were analyzed. The distances between the outermost injury and outermost end of “reference isodose length” (RIL), defined as a segment with ≥90% of reference dose at 1 mm vessel wall depth, were measured. “Safety margin” was defined as the distance between the outermost injury and outermost end of the RIL, “geographical miss” (GM) as a complete injured segment not being covered by the RIL, and “restenosis” as the percent diameter stenosis >50%.ResultsBaseline angiographic analysis was performed for 224 edges in 112 vessels. Geographical miss was found in 46 (20.6%) edges. The incidence of target lesion restenosis within the 78 vessels with available follow-up was 43.3% for patients with GM versus 14.9% for patients with no GM (p = 0.005). Analysis of various injured segments exposed highest restenosis rates in injured segments with negligible irradiation (27.8%) in comparison with injured segments with dose fall-off (16.7%) or injured segments with full-dose irradiation (7.7%) (p = 0.006). Receiver operating curve analysis revealed a safety margin of 10 mm required per vessel (i.e., 5-mm safety margin/edge) to achieve 95% specificity of GM.ConclusionsGeographical miss is associated with a higher incidence of restenosis at the corresponding edges. Restenosis was more pronounced in injured segments with negligible irradiation than in injured segments at the dose fall-off zones. We recommend a safety margin of 10 mm per vessel to minimize GM

    Adaptive, hands-off stream mining

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    Sensor devices and embedded processors are becoming ubiquitous, especially in measurement and monitoring applications. Automatic discovery of patterns and trends in the large volumes of such data is of paramount importance. The combination of relatively limited resources (CPU, memory and/or communication bandwidth and power) poses some interesting challenges. We need both powerful and concise “languages ” to represent the important features of the data, which can (a) adapt and handle arbitrary periodic components, including bursts, and (b) require little memory and a single pass over the data. This allows sensors to automatically (a) discover interesting patterns and trends in the data, and (b) perform outlier detection to alert users. We need a way so that a sensor can discover something like “the hourly phone call volume so far follows a daily and a weekly periodicity, with bursts roughly every year, ” which a human might recognize as, e.g., the Mother’s day surge. When possible and if desired, the user can then issue explicit queries to further investigate the reported patterns. In this work we propose AWSOM (Arbitrary Window Stream mOdeling Method), which allows sensors operating in remote or hostile environments to discover patterns efficiently an
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