340 resultados para Single-item


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A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.

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The purpose of this study was to determine the threshold of exercise energy expenditure necessary to change blood lipid and lipoprotein concentrations and lipoprotein lipase activity (LPLA) in healthy, trained men. On different days, 11 men (age, 26.7 +/- 6.1 yr; body fat, 11.0 +/- 1.5%) completed four separate, randomly assigned, submaximal treadmill sessions at 70% maximal O-2 consumption. During each session 800, 1,100, 1,300, or 1,500 kcal were expended. Compared with immediately before exercise, high-density lipoprotein cholesterol (HDL-C) concentration was significantly elevated 24 h after exercise (P < 0.05) in the 1,100-, 1,300-, and 1,500-kcal sessions. HDL-C concentration was also elevated (P < 0.05) immediately after and 48 h after exercise in the 1,500-kcal session. Compared with values 24 h before exercise, LPLA. was significantly greater (P < 0.05) 24 h after exercise in the 1,100-, 1,300-, and 1,500-kcal sessions and remained elevated 48 h after exercise in the 1,500-kcal session. These data indicate that, in healthy, trained men, 1,100 kcal of energy expenditure are necessary to elicit increased HDL-C concentrations. These HDL-C changes coincided with increased LPLA.

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Aim To establish the suitability of multiplex tandem polymerase chain reaction (MT-PCR) for rapid identification of oestrogen receptor (ER) and Her-2 status using a single, formalin-fixed, paraffin-embedded (FFPE) breast tumour section. Methods Tissue sections from 29 breast tumours were analysed by immunohistochemistry (IHC) and fluorescence in situ hybridisation (FISH). RNA extracted from 10μm FFPE breast tumour sections from 24 of 29 tumours (14 ER positive and 5 Her-2 positive) was analysed by MT-PCR. After establishing a correlation between IHC and/or FISH and MT-PCR results, the ER/Her-2 status of a further 32 randomly selected, archival breast tumour specimens was established by MT-PCR in a blinded fashion, and compared to IHC/FISH results. Results MT-PCR levels of ER and Her-2 showed good concordance with IHC and FISH results. Furthermore, among the ER positive tumours, MT-PCR provided a quantitative score with a high dynamic range. Threshold values obtained from this data set applied to 32 archival tumour specimens showed that tumours strongly positive for ER and/or Her-2 expression were easily identified by MT-PCR. Conclusion MT-PCR can provide rapid, sensitive and cost-effective analysis of FFPE material and may prove useful as triage to identify patients suited to endocrine or trastuzumab (Herceptin) treatment.

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An experiment was conducted to investigate the process of reasoning about directions in an egocentric space. Each participant walked through a corridor containing an angular turn ranging in size from 0° to 90°, in 15° increments. A direction was given to participants at the entrance of the corridor and they were asked to answer this direction at the end of this corridor. Considering the fact that participants had to reason the direction in the featureless corridor, two hypotheses were proposed: (i) reasoning about directions falls into qualitative reasoning by using a small number of coarse angular categories (four 90° categories or eight 45° categories: 90° categories consist of front, back, left, right; 45° categories consist of 90° categories and the four intermediates) that reference axes generate; (ii) reasoning about directions would be done by recalling the rotation angle from the traveling direction to the direction that participants tried to answer. In addition, the configuration of reference axes that participants employed was examined. Both hypotheses were supported, and the data designated that reference axes consisted of eight directions: a pair of orthogonal axes and diagonals.

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Graphene grown on metal catalysts with low carbon solubility is a highly competitive alternative to exfoliated and other forms of graphene, yet a single-layer, single-crystal structure remains a challenge because of the large number of randomly oriented nuclei that form grain boundaries when stitched together. A kinetic model of graphene nucleation and growth is developed to elucidate the effective controls of the graphene island density and surface coverage from the onset of nucleation to the full monolayer formation in low-pressure, low-temperature CVD. The model unprecedentedly involves the complete cycle of the elementary gas-phase and surface processes and shows a precise quantitative agreement with the recent low-energy electron diffraction measurements and also explains numerous parameter trends from a host of experimental reports. These agreements are demonstrated for a broad pressure range as well as different combinations of precursor gases and supporting catalysts. The critical role of hydrogen in controlling the graphene nucleation and monolayer formation is revealed and quantified. The model is generic and can be extended to even broader ranges of catalysts and precursor gases/pressures to enable the as yet elusive effective control of the crystalline structure and number of layers of graphene using the minimum amounts of matter and energy.

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Precisely controlled reactive chemical vapor synthesis of highly uniform, dense arrays of vertically aligned single-walled carbon nanotubes (SWCNTs) using tailored trilayered Fe/Al2O3/SiO2 catalyst is demonstrated. More than 90% population of thick nanotubes (>3 nm in diameter) can be produced by tailoring the thickness and microstructure of the secondary catalyst supporting SiO2 layer, which is commonly overlooked. The proposed model based on the atomic force microanalysis suggests that this tailoring leads to uniform and dense arrays of relatively large Fe catalyst nanoparticles on which the thick SWCNTs nucleate, while small nanotubes and amorphous carbon are effectively etched away. Our results resolve a persistent issue of selective (while avoiding multiwalled nanotubes and other carbon nanostructures) synthesis of thick vertically aligned SWCNTs whose easily switchable thickness-dependent electronic properties enable advanced applications in nanoelectronic, energy, drug delivery, and membrane technologies.

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Diverse morphologies of multidimensional hierarchical single-crystalline ZnO nanoarchitectures including nanoflowers, nanobelts, and nanowires are obtained by use of a simple thermal evaporation and vapour-phase transport deposition technique by placing Au-coated silicon substrates in different positions inside a furnace at process temperatures as low as 550 °C. The nucleation and growth of ZnO nanostructures are governed by the vapour–solid mechanism, as opposed to the commonly reported vapour–liquid–solid mechanism, when gold is used in the process. The morphological, structural, compositional and optical properties of the synthesized ZnO nanostructures can be effectively tailored by means of the experimental parameters, and these properties are closely related to the local growth temperature and gas-phase supersaturation at the sample position. In particular, room-temperature photoluminescence measurements reveal an intense near-band-edge ultraviolet emission at about 386 nm for nanobelts and nanoflowers, which suggests that these nanostructures are of sufficient quality for applications in, for example, optoelectronic devices.

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We report the catalyst-free synthesis of the arrays of core–shell, ultrathin, size-uniform SiC/AlSiC nanowires on the top of a periodic anodic aluminum oxide template. The nanowires were grown using an environmentally friendly, silane-free process by exposing the silicon supported porous alumina template to CH4 + H2 plasmas. High-resolution scanning and transmission electron microscopy studies revealed that the nanowires have a single-crystalline core with a diameter of about 10 nm and a thin (1–2 nm) amorphous AlSiC shell. Because of their remarkable length, high aspect ratio, and very high surface area-to-volume ratio, these unique structures are promising for nanoelectronic and nanophotonic applications that require efficient electron emission, light scattering, etc. A mechanism for nanowire growth is proposed based upon the reduction of the alumina template to nanosized metallic aluminum droplets forming between nanopores. The subsequent incorporation of silicon and carbon atoms from the plasma leads to nucleation and growth from the top of the alumina template.

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Highly efficient solar cells (conversion efficiency 11.9%, fill factor 70%) based on the vertically aligned single-crystalline nanostructures are fabricated without any pre-fabricated p-n junctions in a very simple, single-step process of Si nanoarray formation by etching p-type Si(100) wafers in low-temperature environment-friendly plasmas of argon and hydrogen mixtures.

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Multiscale, multiphase numerical modeling is used to explain the mechanisms of effective control of chirality distributions of single-walled carbon nanotubes in direct plasma growth and suggest effective approaches to further improvement. The model includes an unprecedented combination of the plasma sheath, ion/radical transport, species creation/loss, plasma–surface interaction, heat transfer, surface/bulk diffusion, graphene layer nucleation, and bending/lift-off modules. It is shown that the constructive interplay between the plasma and the Gibbs–Thomson effect can lead to the effective nucleation and lift-off of small graphene layers on small metal catalyst nanoparticles. As a result, much thinner nanotubes with narrower chirality distributions can nucleate at much lower process temperatures and pressures compared to thermal CVD. This approach is validated by a host of experimental results, substantially reduces the amounts of energy and atomic matter required for the nanotube growth, and can be extended to other nanoscale structures and materials systems, thereby nearing the ultimate goal of energy- and matter-efficient nanotechnology.

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Tailoring the density of random single-walled carbon nanotube (SWCNT) networks is of paramount importance for various applications, yet it remains a major challenge due to the insufficient catalyst activation in most growth processes. Here we report on a simple and effective method to maximise the number of active catalyst nanoparticles using catalytic chemical vapor deposition (CCVD). By modulating short pulses of acetylene into a methane-based CCVD growth process, the density of SWCNTs is dramatically increased by up to three orders of magnitude without increasing the catalyst density and degrading the nanotube quality. In the framework of a vapor-liquid-solid model, we attribute the enhanced growth to the high dissociation rate of acetylene at high temperatures at the nucleation stage, which can be effective in both supersaturating the larger catalyst nanoparticles and overcoming the nanotube nucleation energy barrier of the smaller catalyst nanoparticles. These results are highly relevant to numerous applications of random SWCNT networks in next-generation energy, sensing and biomedical devices. © 2011 The Royal Society of Chemistry.

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Controlled synthesis of both single-walled carbon nanotube and carbon nanowire networks using the same CVD reactor and Fe/Al2O3 catalyst by slightly altering the hydrogenation and temperature conditions is demonstrated. Structural, bonding and electrical characterization using SEM, TEM, Raman spectroscopy, and temperature-dependent resistivity measurements suggest that the nanotubes are of a high quality and a large fraction (well above the common 33% and possibly up to 75%) of them are metallic. On the other hand, the carbon nanowires are amorphous and semiconducting and feature a controlled sp2/sp3 ratio. The growth mechanism which is based on the catalyst nanoisland analysis by AFM and takes into account the hydrogenation and temperature control effects explains the observed switch-over of the nanostructure growth modes. These results are important to achieve the ultimate control of chirality, structure, and conductivity of one-dimensional all-carbon networks.

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The electronic transport in both intrinsic and acid-treated single-walled carbon nanotube networks containing more than 90% semiconducting nanotubes is investigated using temperature-dependent resistance measurements. The semiconducting behavior observed in the intrinsic network is attributed to the three-dimensional electron hopping mechanism. In contrast, the chemical doping mechanism in the acid-treated network is found to be responsible for the revealed metal-like linear resistivity dependence in a broad temperature range. This effective method to control the electrical conductivity of single-walled carbon nanotube networks is promising for future nanoscale electronics, thermometry, and bolometry. © 2010 American Institute of Physics.

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Synthesis of one-dimensional AlN nanostructures commonly requires high process temperatures (>900 °C), metal catalyst, and hazardous gas/powder precursors. We report on a simple, single-step, catalyst-free, plasma-assisted growth of dense patterns of size-uniform single-crystalline AlN nanorods at a low substrate temperature (∼650 °C) without any catalyst or hazardous precursors. This unusual growth mechanism is based on highly effective plasma dissociation of N2 molecules, localized species precipitation on AlN islands, and reduced diffusion on the nitrogen-rich surface. This approach can also be used to produce other high-aspect-ratio oxide and nitride nanostructures for applications in energy conversion, sensing, and optoelectronics. © 2010 American Institute of Physics.

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It is demonstrated that a magnetic field has a profound effect on the length of a single-wall carbon nanotube (SWCNT) synthesized in the arc discharge. The average length of SWCNT increases by a factor of 2 in discharge with magnetic field as compared with the discharge without magnetic field, and the yield of long nanotubes with lengths above 5 μm also increases. A model of SWCNT growth on metal catalyst in arc plasma was developed. Monte-Carlo simulations confirm that the increase of the plasma density in the magnetic field leads to an increase in the nanotube growth rate and thus leads to longer nanotubes.