815 resultados para Reversible Computing
Resumo:
We use ellipsometry to investigate a transition in the morphology of a sphere-forming diblock copolymer thin-film system. At an interface the diblock morphology may differ from the bulk when the interfacial tension favours wetting of the minority domain, thereby inducing a sphere-to-lamella transition. In a small, favourable window in energetics, one may observe this transition simply by adjusting the temperature. Ellipsometry is ideally suited to the study of the transition because the additional interface created by the wetting layer affects the polarisation of light reflected from the sample. Here we study thin films of poly(butadiene-ethylene oxide) (PB-PEO), which order to form PEO minority spheres in a PB matrix. As temperature is varied, the reversible transition from a partially wetting layer of PEO spheres to a full wetting layer at the substrate is investigated.
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Analogue computers provide actual rather than virtual representations of model systems. They are powerful and engaging computing machines that are cheap and simple to build. This two-part Retronics article helps you build (and understand!) your own analogue computer to simulate the Lorenz butterfly that's become iconic for Chaos theory.
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Several new coordinatively unsaturated iron(II) complexes of the types [Fe(EN-iPr)X2] (E = P, S, Se; X = Cl, Br) and [Fe(ON-iPr)2X]X containing bidentate EN ligands based on N-(2-pyridinyl)aminophosphines as well as oxo, thio, and seleno derivatives thereof were prepared and characterized by NMR spectroscopy and X-ray crystallography. Mössbauer spectroscopy and magnetization studies confirmed their high-spin nature with magnetic moments very close to 4.9 μB, reflecting the expected four unpaired d-electrons in all these compounds. Stable low-spin carbonyl complexes of the types [Fe(PN-iPr)2(CO)X]X (X = Cl, Br) and cis-CO,cis-Br-[Fe(PN-iPr)(CO)2X2] (X = Br) were obtained by reacting cis-Fe(CO)4X2 with the stronger PN donor ligands, but not with the weaker EN donor ligands (E = O, S, Se). Furthermore, the reactivity of [Fe(PN-iPr)X2] toward CO was investigated by IR spectroscopy. Whereas at room temperature no reaction took place, at −50 °C [Fe(PN-iPr)X2] added readily CO to form, depending on the nature of X, the mono- and dicarbonyl complexes [Fe(PN-iPr)(X)2(CO)] (X = Cl) and [Fe(PN-iPr)(CO)2X2] (X = Cl, Br), respectively. In the case of X = Br, two isomeric dicarbonyl complexes, namely, cis-CO,trans-Br-[Fe(PN-iPr)(CO)2Br2] (major species) and cis-CO,cis-Br-[Fe(PN-iPr)(CO)2Br2] (minor species), are formed. The addition of CO to [Fe(PN-iPr)X2] was investigated in detail by means of DFT/B3LYP calculations. This study strongly supports the experimental findings that at low temperature two isomeric low-spin dicarbonyl complexes are formed. For kinetic reasons cis,trans-[Fe(PN-iPr)(CO)2Br2] releases CO at elevated temperature, re-forming [Fe(PN-iPr)Br2], while the corresponding cis,cis isomer is stable under these conditions.
Resumo:
Markowitz showed that assets can be combined to produce an 'Efficient' portfolio that will give the highest level of portfolio return for any level of portfolio risk, as measured by the variance or standard deviation. These portfolios can then be connected to generate what is termed an 'Efficient Frontier' (EF). In this paper we discuss the calculation of the Efficient Frontier for combinations of assets, again using the spreadsheet Optimiser. To illustrate the derivation of the Efficient Frontier, we use the data from the Investment Property Databank Long Term Index of Investment Returns for the period 1971 to 1993. Many investors might require a certain specific level of holding or a restriction on holdings in at least some of the assets. Such additional constraints may be readily incorporated into the model to generate a constrained EF with upper and/or lower bounds. This can then be compared with the unconstrained EF to see whether the reduction in return is acceptable. To see the effect that these additional constraints may have, we adopt a fairly typical pension fund profile, with no more than 20% of the total held in Property. The paper shows that it is now relatively easy to use the Optimiser available in at least one spreadsheet (EXCEL) to calculate efficient portfolios for various levels of risk and return, both constrained and unconstrained, so as to be able to generate any number of Efficient Frontiers.
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Here we explore the physico-chemical properties of a peptide amphiphile obtained by chemical conjugation of the collagenstimulating peptide KTTKS with 10,12-pentacosadiynoic acid which photopolymerizes as a stable and extended polydiacetylene. We investigate the self-assembly of this new polymer and rationalize its peculiar behavior in terms of a thermal conformational transition. Surprisingly, this polymer shows a thermal transition associated with a non-cooperative increase in b-sheet content at high temperature.
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Abstract. We prove that the vast majority of JC∗-triples satisfy the condition of universal reversibility. Our characterisation is that a JC∗-triple is universally reversible if and only if it has no triple homomorphisms onto Hilbert spaces of dimension greater than two nor onto spin factors of dimension greater than four. We establish corresponding characterisations in the cases of JW∗-triples and of TROs (regarded as JC∗-triples). We show that the distinct natural operator space structures on a universally reversible JC∗-triple E are in bijective correspondence with a distinguished class of ideals in its universal TRO, identify the Shilov boundaries of these operator spaces and prove that E has a unique natural operator space structure precisely when E contains no ideal isometric to a nonabelian TRO. We deduce some decomposition and completely contractive properties of triple homomorphisms on TROs.
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The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.
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Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.
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The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.