851 resultados para Landscape Units


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Two new antimony sulphides have been prepared solvothermally and characterised by single-crystal X-ray diffraction. [Co(en)(3)][Sb4S7] (1) was prepared at 140 degreesC from COS, Sb2S3 and S in the presence of ethylenediamine, whilst heating a mixture of Sb2S3, Co and S in tris(2aminoethyl)amine, N(CH2CH2NH2)(3), at 180 degreesC fegults in the formation of [C6H20N4][Sb4S7] (2). Both materials contain [Sb4S7](2-) chains formed from linkage of cyclic Sb3S63- units by SbS33- pyramids. In (1), the [Sb4S7] chains are linked by secondary Sb-S interactions to form sheets, between which the. charge balancing [Co(en)(3)](2+) cations reside. The structure of (2) involves interconnection of pairs of [Sb4S7](2-) chains through Sb2S2 rings to form isolated [Sb4S7](2-) double chains which are interleaved by protonated template molecules. (C) 2004 Elsevier B.V. All rights resereved.

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This paper details the synthesis, characterisation and physical analyses of a series of hydrogen bonded urethane supramolecular polymer systems that are created by a facile one-step synthesis from inexpensive and commercially available starting materials. We report the synthesis and characterisation of a series of low molecular weight bisurethanes (<650 a.m.u.) that exhibit physical properties in the bulk that are characteristic of polyurethane materials possessing far higher molecular weight. The physical characteristics of these low molecular weight bisurethanes were investigated by using temperature-dependent rheological analysis and viscometry and the nature in which these compounds assembled was assessed using IR and NMR spectroscopies. These studies reveal that these simple bisurethanes self-assemble via hydrogen bonding interactions.

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Bis-[(p-methoxybenzyl)cyclopentadienyl] titanium dichloride, better known as Titanocene Y, is a newly synthesized titanium-based anticancer drug. We studied the antitumor activity of Titanocene Y with concentrations of 2.1, 21 and 210 μmol/l against a range of freshly explanted human tumors, using an in-vitro soft agar cloning system. The sensitivity against Titanocene Y was highly remarkable in the case of renal cell, ovarian, nonsmall cell lung and colon cancer. In particular the surprisingly good response of nonsmall cell lung cancer and colon cancer against Titanocene Y at its lowest concentration of 2.1 μmol/l was well comparable or better with respect to cisplatin, given at a concentration of 1.0 μmol/l. Further clinical development of Titanocene Y appears to be warranted because of the broad cytotoxic activity shown and the specific activity of Titanocene Y against renal cell cancer.

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Space applications are challenged by the reliability of parallel computing systems (FPGAs) employed in space crafts due to Single-Event Upsets. The work reported in this paper aims to achieve self-managing systems which are reliable for space applications by applying autonomic computing constructs to parallel computing systems. A novel technique, 'Swarm-Array Computing' inspired by swarm robotics, and built on the foundations of autonomic and parallel computing is proposed as a path to achieve autonomy. The constitution of swarm-array computing comprising for constituents, namely the computing system, the problem / task, the swarm and the landscape is considered. Three approaches that bind these constituents together are proposed. The feasibility of one among the three proposed approaches is validated on the SeSAm multi-agent simulator and landscapes representing the computing space and problem are generated using the MATLAB.

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The Learning Landscape project described here is known as RedGloo and has several objectives; among others it aims to help students to make friends, contacts and join communities based on interests and competencies. RedGloo provides a space where students can support each other with personal, academic and career development, sharing insights gained from extracurricular activities as well as their degree programmes. It has shown tendencies of becoming a learning community with several communities of practice.

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Many evolutionary algorithm applications involve either fitness functions with high time complexity or large dimensionality (hence very many fitness evaluations will typically be needed) or both. In such circumstances, there is a dire need to tune various features of the algorithm well so that performance and time savings are optimized. However, these are precisely the circumstances in which prior tuning is very costly in time and resources. There is hence a need for methods which enable fast prior tuning in such cases. We describe a candidate technique for this purpose, in which we model a landscape as a finite state machine, inferred from preliminary sampling runs. In prior algorithm-tuning trials, we can replace the 'real' landscape with the model, enabling extremely fast tuning, saving far more time than was required to infer the model. Preliminary results indicate much promise, though much work needs to be done to establish various aspects of the conditions under which it can be most beneficially used. A main limitation of the method as described here is a restriction to mutation-only algorithms, but there are various ways to address this and other limitations.