516 resultados para Geometric growth


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This paper addresses of the advanced computational technique of steel structures for both simulation capacities simultaneously; specifically, they are the higher-order element formulation with element load effect (geometric nonlinearities) as well as the refined plastic hinge method (material nonlinearities). This advanced computational technique can capture the real behaviour of a whole second-order inelastic structure, which in turn ensures the structural safety and adequacy of the structure. Therefore, the emphasis of this paper is to advocate that the advanced computational technique can replace the traditional empirical design approach. In the meantime, the practitioner should be educated how to make use of the advanced computational technique on the second-order inelastic design of a structure, as this approach is the future structural engineering design. It means the future engineer should understand the computational technique clearly; realize the behaviour of a structure with respect to the numerical analysis thoroughly; justify the numerical result correctly; especially the fool-proof ultimate finite element is yet to come, of which is competent in modelling behaviour, user-friendly in numerical modelling and versatile for all structural forms and various materials. Hence the high-quality engineer is required, who can confidently manipulate the advanced computational technique for the design of a complex structure but not vice versa.

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The results of a hybrid numerical simulation of the growth kinetics of carbon nanowall-like nanostructures in the plasma and neutral gas synthesis processes are presented. The low-temperature plasma-based process was found to have a significant advantage over the purely neutral flux deposition in providing the uniform size distribution of the nanostructures. It is shown that the nanowall width uniformity is the best (square deviations not exceeding 1.05) in high-density plasmas of 3.0× 1018 m-3, worsens in lower-density plasmas (up to 1.5 in 1.0× 1017 m-3 plasmas), and is the worst (up to 1.9) in the neutral gas-based process. This effect has been attributed to the focusing of ion fluxes by irregular electric field in the vicinity of plasma-grown nanostructures on substrate biased with -20 V potential, and differences in the two-dimensional adatom diffusion fluxes in the plasma and neutral gas-based processes. The results of our numerical simulations are consistent with the available experimental reports on the effect of the plasma process parameters on the sizes and shapes of relevant nanostructures.

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The controlled growth of ultra-small Ge/Si quantum dot (QD) nuclei (≈1 nm) suitable for the synthesis of uniform nanopatterns with high surface coverage, is simulated using atom-only and size non-uniform cluster fluxes. It is found that seed nuclei of more uniform sizes are formed when clusters of non-uniform size are deposited. This counter-intuitive result is explained via adatom-nanocluster interactions on Si(100) surfaces. Our results are supported by experimental data on the geometric characteristics of QD patterns synthesized by nanocluster deposition. This is followed by a description of the role of plasmas as non-uniform cluster sources and the impact on surface dynamics. The technique challenges conventional growth modes and is promising for deterministic synthesis of nanodot arrays.

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Large area, highly uniform vertically aligned carbon nanotips (VACNTP) and other nanostructures have been grown on silicon (100) substrates with Ni catalyst in the low-temperature, low-frequency, high-density inductively coupled plasmas (ICP) of methane-hydrogen-argon gas mixtures. The control strategies for the morphology, crystalline structure and chemical states of the resulting nanostructures by varying the growth conditions are proposed. XRD and Roman analyses confirm that the nanotips are well graphitized, which is favorable for the field emission applications.

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This article examines the extent to which combinations of intellectual resources and product innovation capability, and reputational resources and marketing capability, influence the ability of small and medium-sized enterprises (SME) to meet or exceed performance goals. Empirical results drawn from 171 SMEs suggest that when the combination of intellectual resources and product innovation capability in addition to the combination of reputational resources and marketing capability are high, SME growth is enhanced. However, a high level of intellectual resources combined with a low level of product innovation capability as well as a combination of a high level of reputational resources with a low level of marketing capability (and vice versa) are not significantly related to growth. These results imply that a high level of resources cannot compensate for a low level of capabilities (and vice versa).

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We outline a metal-free fabrication route of in-plane Ge nanowires on Ge(001) substrates. By positively exploiting the polishing-induced defects of standard-quality commercial Ge(001) wafers, micrometer-length wires are grown by physical vapor deposition in ultra-high-vacuum environment. The shape of the wires can be tailored by the epitaxial strain induced by subsequent Si deposition, determining a progressive transformation of the wires in SiGe faceted quantum dots. This shape transition is described by finite element simulations of continuous elasticity and gives hints on the equilibrium shape of nanocrystals in the presence of tensile epitaxial strain.

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This paper examines the effect of anisotropic growth on the evolution of mechanical stresses in a linear-elastic model of a growing, avascular tumour. This represents an important improvement on previous linear-elastic models of tissue growth since it has been shown recently that spatially-varying isotropic growth of linear-elastic tissues does not afford the necessary stress-relaxation for a steady-state stress distribution upon reaching a nutrient-regulated equilibrium size. Time-dependent numerical solutions are developed using a Lax-Wendroff scheme, which show the evolution of the tissue stress distributions over a period of growth until a steady-state is reached. These results are compared with the steady-state solutions predicted by the model equations, and key parameters influencing these steady-state distributions are identified. Recommendations for further extensions and applications of this model are proposed.

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Vascular endothelial growth factor (VEGF) promotes growth of blood or lymphatic vessels. The aim of the current study is to identify relationships between VEGF-A and VEGF-C, and their impact in angiogenesis and metastases in thyroid cancers. VEGF-A and VEGF-C mRNA and protein expression was investigated in 136 thyroid cancers (123 papillary thyroid carcinomas and 13 undifferentiated thyroid carcinomas) and 40 matched lymph node metastases with papillary thyroid carcinoma using reverse transcription polymerase chain reaction and immunohistochemistry. VEGF-A and VEGF-C mRNA expression was significantly different between conventional papillary thyroid carcinoma, follicular variant of papillary thyroid carcinoma, and undifferentiated thyroid carcinomas (P = 1 x 10(-6) and 1 x 10(-5), respectively). In undifferentiated carcinoma, VEGF-A and VEGF-C protein overexpression was noted in all cases. VEGF-A and VEGF-C mRNA overexpression was noted in 51% (n = 62) and 27% (n = 33) of the papillary thyroid carcinomas, whereas VEGF-A and VEGF-C protein overexpression was also identified in 70% (n = 86) and 62% (n = 76) of the carcinomas. VEGF-A mRNA was significantly higher in cancers with lymph node metastases compared with nonmetastatic cancers (P = .001), whereas most metastatic cancers underexpressed VEGF-C (P = .0002), with a similar trend for protein. The expression of VEGF-A and VEGF-C correlated with each other at both mRNA and protein levels (P = .00004 and .003, respectively). In summary, VEGF-A and -C expressions correlate with the pathological parameters and metastatic status of thyroid carcinomas. The significant correlations between the expressions of these genes add weight to hypotheses concerning VEGF-A and -C interaction in cancer progression.

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Background: Cancer metastasis is the main contributor to breast cancer fatalities as women with the metastatic disease have poorer survival outcomes than women with localised breast cancers. There is an urgent need to develop appropriate prognostic methods to stratify patients based on the propensities of their cancers to metastasise. The insulin-like growth factor (IGF)-I:IGF binding protein (IGFBP):vitronectin complexes have been shown to stimulate changes in gene expression favouring increased breast cancer cell survival and a migratory phenotype. We therefore investigated the prognostic potential of these IGF- and extracellular matrix (ECM) interaction-induced proteins in the early identification of breast cancers with a propensity to metastasise using patient-derived tissue microarrays. Methods: Semiquantitative immunohistochemistry analyses were performed to compare the extracellular and subcellular distribution of IGF- and ECM-induced signalling proteins among matched normal, primary cancer and metastatic cancer formalin-fixed paraffin-embedded breast tissue samples. Results: The IGF- and ECM-induced signalling proteins were differentially expressed between subcellular and extracellular localisations. Vitronectin and IGFBP-5 immunoreactivity was lower while β1 integrin immunoreactivity was higher in the stroma surrounding metastatic cancer tissues, as compared to normal breast and primary cancer stromal tissues. Similarly, immunoreactive stratifin was found to be increased in the stroma of primary as well as metastatic breast tissues. Immunoreactive fibronectin and β1 integrin was found to be highly expressed at the leading edge of tumours. Based on the immunoreactivity it was apparent that the cell signalling proteins AKT1 and ERK1/2 shuffled from the nucleus to the cytoplasm with tumour progression. Conclusion: This is the first in-depth, compartmentalised analysis of the distribution of IGF- and ECM-induced signalling proteins in metastatic breast cancers. This study has provided insights into the changing pattern of cellular localisation and expression of IGF- and ECM-induced signalling proteins in different stages of breast cancer. The differential distribution of these biomarkers could provide important prognostic and predictive indicators that may assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy.

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Description Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Contents Contents: Preface Part I: Global Analysis 1. Economic Growth and the Environment 2. Energy Substitution and Carbon Dioxide Emissions 3. Pollution, Natural Resources, and Economic Growth 4. Trade Openness and Environmental Quality 5. Environmental Productivity 6. Energy Price-induced Technological Change 7. Trade-induced Technological Change 8. Regional Economic Integration Part II: Country-Level Analysis 9. Emissions Trading in the United States 10. Increasing Returns to Pollution Abatement in the United States 11. Policy-induced Competitiveness in the United States 12. Trade Liberalization, Technology, and the Environment 13. Policy Implementation and its Effectiveness in China 14. Clean Technological Inventions in Japan 15. Intervention of Economic Policy and its Nonlinear Effects in Japan 16. The Next Emerging Giants: India and Africa 17. Conclusion Index Further information Through a combination of global data analysis and focused country level analysis, this timely book provides answers to the most pertinent country and industry specific questions defining the current relationship between technology, natural resources and economic growth. Shunsuke Managi takes a distinctive approach by focusing on the design and implementation of environmental regulations that encourage technological progress and, in doing so, looks at ways to ensure productivity improvements in the face of increasingly stringent environmental regulations and natural resource depletion. The findings in this important book demonstrate how successful environmental policies can contribute to efficiency by encouraging, rather than inhibiting, technological innovation. Technology, Natural Resources and Economic Growth will provide a valuable resource for a wide readership including postgraduate students, researchers, academics and policy makers working in the fields of environmental and ecological economics.

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The Environmental Kuznets Curve (EKC) hypothesises an inverse U-shaped relationship between a measure of environmental pollution and per capita income levels. In this study, we apply non-parametric estimation of local polynomial regression (local quadratic fitting) to allow more flexibility in local estimation. This study uses a larger and globally representative sample of many local and global pollutants and natural resources including Biological Oxygen Demand (BOD) emission, CO2 emission, CO2 damage, energy use, energy depletion, mineral depletion, improved water source, PM10, particulate emission damage, forest area and net forest depletion. Copyright © 2009 Inderscience Enterprises Ltd.

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While economic theory acknowledges that some features of technology (e.g., indivisibilities, economies of scale and specialization) can fundamentally violate the traditional convexity assumption, almost all empirical studies accept the convexity property on faith. In this contribution, we apply two alternative flexible production technologies to measure total factor productivity growth and test the significance of the convexity axiom using a nonparametric test of closeness between unknown distributions. Based on unique field level data on the petroleum industry, the empirical results reveal significant differences, indicating that this production technology is most likely non-convex. Furthermore, we also show the impact of convexity on answers to traditional convergence questions in the productivity growth literature.

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In this paper, the productivities of Japanese airports over the period of 1987-2005 are analyzed using the Malmquist index, and technological bias is investigated. During this period, airports on average became less efficient and experienced technological regress. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity for Japanese airports.

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This paper investigates the productivity change of Japanese credit banks with a Malmquist index and the input technological bias during 2000-2006. Our results indicate that the traditional growth accounting method, which assumes Hicks neutral technological change, is not appropriate for analyzing changes in productivity. Our analysis unambiguously shows that management of Shinkin banks has to be improved. These must be based on the improvement of technical efficiency and/or technological change, emulating the procedures of the best-practice banks, i.e., those banks with Malmquist productivity scores higher than one and simultaneously with technical efficiency and technological change higher than one.