226 resultados para ABSOLUTE STRUCTURES


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The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

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Micrometre-sized MgB2 crystals of varying quality, synthesized at low temperature and autogeneous pressure, are compared using a combination of Raman and Infra-Red (IR) spectroscopy. These data, which include new peak positions in both spectroscopies for high quality MgB2, are interpreted using DFT calculations on phonon behaviour for symmetry-related structures. Raman and IR activity additional to that predicted by point group analyses of the P6/mmm symmetry are detected. These additional peaks, as well as the overall shapes of calculated phonon dispersion (PD) models are explained by assuming a double super-lattice, consistent with a lower symmetry structure for MgB2. A 2x super-lattice in the c-direction allows a simple correlation of the pair breaking energy and the superconducting gap by activation of corresponding acoustic frequencies. A consistent physical interpretation of these spectra is obtained when the position of a phonon anomaly defines a super-lattice modulation in the a-b plane.

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This paper presents a discussion on the use of MIMO and SISO techniques for identification of the radiation force terms in models for surface vessels. We compare and discuss two techniques recently proposed in literature for this application: time domain identification and frequency domain identification. We compare the methods in terms of estimates model order, accuracy of the fit, use of the available information, and ease of use and implementation.

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We present an approach for the inspection of vertical pole-like infrastructure using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures, such as light and power distribution poles, is a time consuming, dangerous and expensive task with high operator workload. To address these issues, we propose a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. We adopt an Image based Visual Servoing (IBVS) technique using only two line features to stabilise the vehicle with respect to a pole. Visual, inertial and sonar data are used, making the approach suitable for indoor or GPS-denied environments. Results from simulation and outdoor flight experiments demonstrate the system is able to successfully inspect and circumnavigate a pole.

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Eight new dihydro-β-agarofurans, denhaminols A–H (1–8), were isolated from the leaves of the Australian rainforest tree Denhamia celastroides. The chemical structures of 1–8 were elucidated following analysis of 1D/2D NMR and MS data. The absolute configuration of denhaminol A (1) was determined by single-crystal X-ray crystallography. All compounds were evaluated for cytotoxic activity against the human prostate cancer cell line LNCaP, using live-cell imaging and metabolic assays. Denhaminols A (1) and G (7) were also tested for their effects on the lipid content of LNCaP cells. This is the first report of secondary metabolites from D. celastroides.

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Chronic difficulties arising from mild brain injury (TBI) are difficult to predict because the processes underlying changes after TBI are poorly understood. In mild brain injury the extent of neuropsychiatric and cognitive symptoms correspond poorly to overt tissue loss (Barth 1983; Liu 2010). Cellular, immune and hormonal cascades occurring after injury and continuing during the healing process may impact uninjured brain regions sensitive to the effects of physiological and emotional stress, which receive projections from the injury site. Changes in these most basic properties due to injury or disease have profound implications for virtually every aspect of brain function through disruption of neurotransmitter, neuroendocrine and metabolic systems. In order to screen for changes in transmitter and metabolic activity, in this study we developed Single voxel proton Magnetic Resonance Spectroscopy (1H-MRS) for use in both injured and control animals. We first evaluated if 1H-MRS could be used to evaluate in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus in both control and injured animals after controlled cortical impact injury to the rat prefrontal cortex. We found that metabolite measurements for Myo-Inositol, Choline, creatine, Glutamate+Glutamine, and N-acetyl-acetate are attainable in deep brain structures in vivo in injured and controls rats. We next seek to evaluate longitudinally, in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus during the first month after controlled cortical impact injury to the rat prefrontal cortex. These ongoing studies will provide data on the changes in transmitters and metabolites over time in injured and non-injured subjects. These studies address some of the fundamental questions about how mild brain injury has such diverse effects on overall brain health and function.

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Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

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Railways are an important mode of transportation. They are however large and complex and their construction, management and operation is time consuming and costly. Evidently planning the current and future activities is vital. Part of that planning process is an analysis of capacity. To determine what volume of traffic can be achieved over time, a variety of railway capacity analysis techniques have been created. A generic analytical approach that incorporates more complex train paths however has yet to be provided. This article provides such an approach. This article extends a mathematical model for determining the theoretical capacity of a railway network. The main contribution of this paper is the modelling of more complex train paths whereby each section can be visited many times in the course of a train’s journey. Three variant models are formulated and then demonstrated in a case study. This article’s numerical investigations have successively shown the applicability of the proposed models and how they may be used to gain insights into system performance.

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The structures of the cocrystalline adducts of 3,5-dinitrobenzoic acid (3,5-DNBA) with 4-aminosalicylic acid (PASA), the 1:1 partial hydrate, C7H4N2O6 .C7H7NO3 . 2H2O, (I) and 2-hydroxy-3-(1H-indol-3-yl)propenoic acid (HIPA) and the 1:1:1 d6-dimethylsulfoxide solvate, C7H4N2O6 . C11H9NO3 . C2D6OS, (II) are reported. The crystal substructure of (I) comprises two centrosymmetric hydrogen-bonded R2/2(8) homodimers, one with 3,5-DNBA, the other with PASA, and an R2/2(8) 3,5-DNBA-PASA heterodimer. In the crystal, inter-unit amine N-H...O and water O-H...O hydrogen bonds generate a three-dimensional supramolecular structure. In (II), the asymmetric unit consists of the three constituent molecules which form an essentially planar cyclic hydrogen-bonded heterotrimer unit [graph set R2/3(17)] through carboxyl, hydroxy and amino groups. These units associate across a crystallographic inversion centre through the HIPA carboxylic acid group in an R2/2~(8) hydrogen-bonding association, giving a zero-dimensional structure lying parallel to (100). In both structures, pi--pi interactions are present [minimum ring centroid separations: 3.6471(18)A in (I) and 3.5819(10)A in (II)].