992 resultados para Drell-Yan


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Many studies have focused on why deliberative institutions should be established in order to develop Chinese people’s citizenry skills; however few focus on the social conditions and public sentiments that shape the development of deliberative mechanisms. Skills and awareness of citizenry is not only brought into being by deliberative institutions that are set up by the government, but evolve through interplays between technologies and social changes. As a test-bed for economic reform Guangdong is increasingly identified by translocality and hybrid culture. This is framed by identity conflict and unrests, much of which is due to soaring wealth polarisation, high volumes of population movement, cultural collisions and ongoing linguistic contestations. These unrests show the region’s transformation goes beyond the economic front. Profound changes are occurring at what anthropologists and philosophers call the changing social conciseness or moral landscape (Ci, 1994; Yan, 2010). The changing social moralities are a reflection of the awareness of individuals’ rights and responsibilities, and their interdependencies from dominant ideologies. This paper discusses Guangdong’s social and cultural characteristics, and questions how existing social conditions allow the staging of political deliberation by facilitating political engagement and the formation of public opinion. The paper will investigate the tragedy of Xiao Yueyue in Foshan, Guangdong, where ‘right’ and ‘responsibility’, ‘self’ and ‘other’ define the public sentiments of deliberation and participation.

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Control of biospecimen quality that is linked to processing is one of the goals of biospecimen science. Consensus is lacking, however, regarding optimal sample quality-control (QC) tools (ie, markers and assays). The aim of this review was to identify QC tools, both for fluid and solid-tissue samples, based on a comprehensive and critical literature review. The most readily applicable tools are those with a known threshold for the preanalytical variation and a known reference range for the QC analyte. Only a few meaningful markers were identified that meet these criteria, such as CD40L for assessing serum exposure at high temperatures and VEGF for assessing serum freeze-thawing. To fully assess biospecimen quality, multiple QC markers are needed. Here we present the most promising biospecimen QC tools that were identified.

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In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.

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Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.

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Graphene has attracted considerable interest over recent years due to its intrinsic mechanical, thermal and electrical properties. Incorporation of small quantity of graphene fillers into polymer can create novel nanocomposites with improved structural and functional properties. This review introduced the recent progress in fabrication, properties and potential applications of graphene-polymer composites. Recent research clearly confirmed that graphene-polymer nanocomposites are promising materials with applications ranging from transportation, biomedical systems, sensors, electrodes for solar cells and electromagnetic interference. In addition to graphene-polymer nanocomposites, this article also introduced the synergistic effects of hybrid graphene-carbon nanotubes (CNTs) on the properties of composites. Finally, some technical problems associated with the development of these nanocomposites are discussed.

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Metal and semiconductor nanowires (NWs) have been widely employed as the building blocks of the nanoelectromechanical systems, which usually acted a resonant beam. Recent researches reported that nanowires are often polycrystalline, which contains grain boundaries (GBs) that transect the whole nanowire into a bamboo like structure. Based on the larger-scale molecular dynamics (MD) simulations, a comprehensive investigation of the influence from grain boundaries on the vibrational properties of doubly clamped Ag NWs is conducted. It is found that, the presence of grain boundary will result in significant energy dissipation during the resonance of polycrystalline NWs, which leads a great deterioration to the quality factor. Further investigation reveals that the energy dissipation is originated from the plastic deformation of polycrystalline NWs in the form of the nucleation of partial dislocations or the generation of micro stacking faults around the GBs and the micro stacking faults is found to keep almost intact during the whole vibration process. Moreover, it is observed that the closer of the grain boundary getting to the regions with the highest strain state, the more energy dissipation will be resulted from the plastic deformation. In addition, either the increase of the number of grain boundaries or the decrease of the distance between the grain boundary and the highest strain state region is observed to induce a lower first resonance frequency. This work sheds lights on the better understanding of the mechanical properties of polycrystalline NWs, which benefits the increasing utilities of NWs in diverse nano-electronic devices.

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Relevance feature and ontology are two core components to learn personalized ontologies for concept-based retrievals. However, how to associate user native information with common knowledge is an urgent issue. This paper proposes a sound solution by matching relevance feature mined from local instances with concepts existing in a global knowledge base. The matched concepts and their relations are used to learn personalized ontologies. The proposed method is evaluated elaborately by comparing it against three benchmark models. The evaluation demonstrates the matching is successful by achieving remarkable improvements in information filtering measurements.

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A newly developed computational approach is proposed in the paper for the analysis of multiple crack problems based on the eigen crack opening displacement (COD) boundary integral equations. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix to determine all the unknown CODs step by step. To deal with the interactions among cracks for multiple crack problems, all cracks in the problem are divided into two groups, namely the adjacent group and the far-field group, according to the distance to the current crack in consideration. The adjacent group contains cracks with relatively small distances but strong effects to the current crack, while the others, the cracks of far-field group are composed of those with relatively large distances. Correspondingly, the eigen COD of the current crack is computed in two parts. The first part is computed by using the fictitious tractions of adjacent cracks via the local Eshelby matrix derived from the traction boundary integral equations in discretized form, while the second part is computed by using those of far-field cracks so that the high computational efficiency can be achieved in the proposed approach. The numerical results of the proposed approach are compared not only with those using the dual boundary integral equations (D-BIE) and the BIE with numerical Green's functions (NGF) but also with those of the analytical solutions in literature. The effectiveness and the efficiency of the proposed approach is verified. Numerical examples are provided for the stress intensity factors of cracks, up to several thousands in number, in both the finite and infinite plates.

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Finding and labelling semantic features patterns of documents in a large, spatial corpus is a challenging problem. Text documents have characteristics that make semantic labelling difficult; the rapidly increasing volume of online documents makes a bottleneck in finding meaningful textual patterns. Aiming to deal with these issues, we propose an unsupervised documnent labelling approach based on semantic content and feature patterns. A world ontology with extensive topic coverage is exploited to supply controlled, structured subjects for labelling. An algorithm is also introduced to reduce dimensionality based on the study of ontological structure. The proposed approach was promisingly evaluated by compared with typical machine learning methods including SVMs, Rocchio, and kNN.

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Graphene nanoribbon (GNR) with free edges demonstrates unique pre-existing edge energy and edge stress, leading to non-flat morphologies. Using molecular dynamics (MD) methods, we evaluated edge energies as well as edge stresses for four different edge types, including regular edges (armchair and zigzag), armchair edge terminated with hydrogen and reconstructed armchair. The results showed that compressive stress exists in the regular and hydrogen-terminated edges along the edge direction. In contrast, the reconstructed armchair edge is generally subject to tension. Furthermore, we also investigated shape transition between flat and rippled configurations of GNRs with different free edges. It was found that the pre-existing stress at free edges can greatly influence the initial energy state and the shape transition.

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Compared to conventional metal-foil strain gauges, nanocomposite piezoresistive strain sensors have demonstrated high strain sensitivity and have been attracting increasing attention in recent years. To fulfil their ultimate success, the performance of vapor growth carbon fiber (VGCF)/epoxy nanocomposite strain sensors subjected to static cyclic loads was evaluated in this work. A strain-equivalent quantity (resistance change ratio) in cantilever beams with intentionally induced notches in bending was evaluated using the conventional metal-foil strain gauges and the VGCF/epoxy nanocomposite sensors. Compared to the metal-foil strain gauges, the nanocomposite sensors are much more sensitive to even slight structural damage. Therefore, it was confirmed that the signal stability, reproducibility, and durability of these nanocomposite sensors are very promising, leading to the present endeavor to apply them for static structural health monitoring.

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In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.

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Cu/Ni/W nanolayered composites with individual layer thickness ranging from 5nm to 300nm were prepared by a magnetron sputtering system. Microstructures and strength of the nanolayered composites were investigated by using the nanoindentation method combined with theoretical analysis. Microstructure characterization revealed that the Cu/Ni/W composite consists of a typical Cu/Ni coherent interface and Cu/W and Ni/W incoherent interfaces. Cu/Ni/W composites have an ultrahigh strength and a large strengthening ability compared with bi-constituent Cu–X(X¼Ni, W, Au, Ag, Cr, Nb, etc.) nanolayered composites. Summarizing the present results and those reported in the literature, we systematically analyze the origin of the ultrahigh strength and its length scale dependence by taking into account the constituent layer properties, layer scales and heterogeneous layer/layer interface characteristics, including lattice and modulus mismatch as well as interface structure.

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Plastic deformation behavior of Cu/Ni/Wmetallicmultilayers with individual layer thickness ranging from 5 nm to 300 nm is investigated by nanoindentation testing. The experimental results reveal that the composite still exhibits indentation-induced plastic deformation instability and the loss of strain hardening ability at the nanometer scale even if the composite contains two kinds of layer interfaces (face centered cubic(FCC)/FCC and FCC/ body centered cubic) simultaneously. Plastic deformation behavior of the nanolayered material was evaluated and analyzed.

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In this work, the thermal expansion properties of carbon nanotube (CNT)-reinforced nanocomposites with CNT content ranging from 1 to 15 wt% were evaluated using a multi-scale numerical approach, in which the effects of two parameters, i.e., temperature and CNT content, were investigated extensively. For all CNT contents, the obtained results clearly revealed that within a wide low-temperature range (30°C ~ 62°C), thermal contraction is observed, while thermal expansion occurs in a high-temperature range (62°C ~ 120°C). It was found that at any specified CNT content, the thermal expansion properties vary with temperature - as temperature increases, the thermal expansion rate increases linearly. However, at a specified temperature, the absolute value of the thermal expansion rate decreases nonlinearly as the CNT content increases. Moreover, the results provided by the present multi-scale numerical model were in good agreement with those obtained from the corresponding theoretical analyses and experimental measurements in this work, which indicates that this multi-scale numerical approach provides a powerful tool to evaluate the thermal expansion properties of any type of CNT/polymer nanocomposites and therefore promotes the understanding on the thermal behaviors of CNT/polymer nanocomposites for their applications in temperature sensors, nanoelectronics devices, etc.