Growth of carbon nanocone arrays on a metal catalyst: The effect of carbon flux ionization

The growth of carbon nanocone arrays on metal catalyst particles by deposition from a low-temperature plasma is studied by multiscale Monte Carlo/surface diffusion numerical simulation. It is demonstrated that the variation in the degree of ionization of the carbon flux provides an effective control of the growth kinetics of the carbon nanocones, and leads to the formation of more uniform arrays of nanostructures. In the case of zero degree of ionization (neutral gas process), a width of the distribution of nanocone heights reaches 360 nm with the nanocone mean height of 150 nm. When the carbon flux of 75% ionization is used, the width of the distribution of nanocone heights decreases to 100 nm, i.e., by a factor of 3.6. A higher degree of ionization leads to a better uniformity of the metal catalyst saturation and the nanocone growth, thus contributing to the formation of more height-uniform arrays of carbon nanostructures.

Multi-scale hybrid numerical simulation of the growth of high-aspect-ratio nanostructures

Recently, a variety high-aspect-ratio nanostructures have been grown and profiled for various applications ranging from field emission transistors to gene/drug delivery devices. However, fabricating and processing arrays of these structures and determining how changing certain physical parameters affects the final outcome is quite challenging. We have developed several modules that can be used to simulate the processes of various physical vapour deposition systems from precursor interaction in the gas phase to gas-surface interactions and surface processes. In this paper, multi-scale hybrid numerical simulations are used to study how low-temperature non-equilibrium plasmas can be employed in the processing of high-aspect-ratio structures such that the resulting nanostructures have properties suitable for their eventual device application. We show that whilst using plasma techniques is beneficial in many nanofabrication processes, it is especially useful in making dense arrays of high-aspect-ratio nanostructures.

Growth kinetics of carbon nanowall-like structures in low-temperature plasmas

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.

Low-temperature growth of large area, vertically aligned carbon nanotubes for field emission applications

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.

The role of intellectual resources, product innovation capability, reputational resources and marketing capability combinations in SME growth

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).

Beneficial defects : exploiting the intrinsic polishing-induced wafer roughness for the catalyst-free growth of Ge in-plane nanowires

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.

A linear-elastic model of anisotropic tumour growth

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.

Temperature variability and childhood pneumonia : an ecological study

Background Few data on the relationship between temperature variability and childhood pneumonia are available. This study attempted to fill this knowledge gap. Methods A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantify the impacts of diurnal temperature range (DTR) and temperature change between two neighbouring days (TCN) on emergency department visits (EDVs) for childhood pneumonia in Brisbane, from 2001 to 2010, after controlling for possible confounders. Results An adverse impact of TCN on EDVs for childhood pneumonia was observed, and the magnitude of this impact increased from the first five years (2001–2005) to the second five years (2006–2010). Children aged 5–14 years, female children and Indigenous children were particularly vulnerable to TCN impact. However, there was no significant association between DTR and EDVs for childhood pneumonia. Conclusions As climate change progresses, the days with unstable weather pattern are likely to increase. Parents and caregivers of children should be aware of the high risk of pneumonia posed by big TCN and take precautionary measures to protect children, especially those with a history of respiratory diseases, from climate impacts.

Co-regulatory potential of vascular endothelial growth factor–A and vascular endothelial growth factor–C in thyroid carcinoma

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.

Differential subcellular and extracellular localisations of proteins required for insulin-like growth factor- and extracellular matrix-induced signalling events in breast cancer progression

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.

Climate variability, climate change and land degradation

Effective response by government and individuals to the risk of land degradation requires an understanding of regional climate variations and the impacts of climate and management on condition and productivity of land and vegetation resources. Analysis of past land degradation and climate variability provides some understanding of vulnerability to current and future climate changes and the information needs for more sustainable management. We describe experience in providing climate risk assessment information for managing for the risk of land degradation in north-eastern Australian arid and semi-arid regions used for extensive grazing. However, we note that information based on historical climate variability, which has been relied on in the past, will now also have to factor in the influence of human-induced climate change. Examples illustrate trends in climate for Australia over the past decade and the impacts on indicators of resource condition. The analysis highlights the benefits of insights into past trends and variability in rainfall and other climate variables based on extended historic databases. This understanding in turn supports more reliable regional climate projections and decision support information for governments and land managers to better manage the risk of land degradation now and in the future.

Technology, Natural Resources and Economic Growth: Improving the Environment for a Greener Future

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.

World emissions and economic growth: Application of non-parametric methods

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.

Total factor productivity growth and convergence in the petroleum industry : empirical analysis testing for convexity

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.