Grassland management activity data : current sources and future needs

Estimates of potential and actual C sequestration require areal information about various types of management activities. Forest surveys, land use data, and agricultural statistics contribute information enabling calculation of the impacts of current and historical land management on C sequestration in biomass (in forests) or in soil (in agricultural systems). Unfortunately little information exists on the distribution of various management activities that can impact soil C content in grassland systems. Limited information of this type restricts our ability to carry out bottom-up estimates of the current C balance of grasslands or to assess the potential for grasslands to act as C sinks with changes in management. Here we review currently available information about grassland management, how that information could be related to information about the impacts of management on soil C stocks, information that may be available in the future, and needs that remain to be filled before in-depth assessments may be carried out. We also evaluate constraints induced by variability in information sources within and between countries. It is readily apparent that activity data for grassland management is collected less frequently and on a coarser scale than data for forest or agricultural inventories and that grassland activity data cannot be directly translated into IPCC-type factors as is done for IPCC inventories of agricultural soils. However, those management data that are available can serve to delineate broad-scale differences in management activities within regions in which soil C is likely to change in response to changes in management. This, coupled with the distinct possibility of more intensive surveys planned in the future, may enable more accurate assessments of grassland C dynamics with higher resolution both spatially and in the number management activities.

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

Mechanical Behavior of Articular Cartilage After Osteochondral Autograft Transfer in an Ovine Model

BACKGROUND: Grafting of autologous hyaline cartilage and bone for articular cartilage repair is a well-accepted technique. Although encouraging midterm clinical results have been reported, no information on the mechanical competence of the transplanted joint surface is available. HYPOTHESIS: The mechanical competence of osteochondral autografts is maintained after transplantation. STUDY DESIGN: Controlled laboratory study. METHODS: Osteochondral defects were filled with autografts (7.45 mm in diameter) in one femoral condyle in 12 mature sheep. The ipsilateral femoral condyle served as the donor site, and the resulting defect (8.3 mm in diameter) was left empty. The repair response was examined after 3 and 6 months with mechanical and histologic assessment and histomorphometric techniques. RESULTS: Good surface congruity and plug placement was achieved. The Young modulus of the grafted cartilage significantly dropped to 57.5% of healthy tissue after 3 months (P < .05) but then recovered to 82.2% after 6 months. The aggregate and dynamic moduli behaved similarly. The graft edges showed fibrillation and, in some cases (4 of 6), hypercellularity and chondrocyte clustering. Subchondral bone sclerosis was observed in 8 of 12 cases, and the amount of mineralized bone in the graft area increased from 40% to 61%. CONCLUSIONS: The mechanical quality of transplanted cartilage varies considerably over a short period of time, potentially reflecting both degenerative and regenerative processes, while histologically signs of both cartilage and bone degeneration occur. CLINICAL RELEVANCE: Both the mechanically degenerative and restorative processes illustrate the complex progression of regeneration after osteochondral transplantation. The histologic evidence raises doubts as to the long-term durability of the osteochondral repair.

Depth-dependent biomechanical and biochemical properties of fetal, newborn, and tissue-engineered articular cartilage

Adult articular cartilage has depth-dependent mechanical and biochemical properties which contribute to zone-specific functions. The compressive moduli of immature cartilage and tissue-engineered cartilage are known to be lower than those of adult cartilage. The objective of this study was to determine if such tissues exhibit depth-dependent compressive properties, and how these depth-varying properties were correlated with cell and matrix composition of the tissue. The compressive moduli of fetal and newborn bovine articular cartilage increased with depth (p < 0.05) by a factor of 4-5 from the top 0.1 mm (28 +/- 13 kPa, 141 +/- 10 kPa, respectively) to 1 mm deep into the tissue. Likewise, the glycosaminoglycan and collagen content increased with depth (both p < 0.001), and correlated with the modulus (both p < 0.01). In contrast, tissue-engineered cartilage formed by either layering or mixing cells from the superficial and middle zone of articular cartilage exhibited similarly soft regions at both construct surfaces, as exemplified by large equilibrium strains. The properties of immature cartilage may provide a template for developing tissue-engineered cartilage which aims to repair cartilage defects by recapitulating the natural development and growth processes. These results suggest that while depth-dependent properties may be important to engineer into cartilage constructs, issues other than cell heterogeneity must be addressed to generate such tissues. (c) 2005 Elsevier Ltd. All rights reserved.

Review: acoustic emission technique - opportunities, challenges and current work at QUT

Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. AE is one of the several non-destructive testing (NDT) techniques currently used for structural health monitoring (SHM) of civil, mechanical and aerospace structures. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. Despite these advantages, several challenges still exist in successful application of AE monitoring. Accurate localization of AE sources, discrimination between genuine AE sources and spurious noise sources and damage quantification for severity assessment are some of the important issues in AE testing and will be discussed in this paper. Various data analysis and processing approaches will be applied to manage those issues.

A study of environmental and management drivers of non-CO2 greenhouse gas emissions in Australian agro-ecosystems

Australian climate, soils and agricultural management practices are significantly different from those of the northern hemisphere nations. Consequently, experimental data on greenhouse gas production from European and North American agricultural soils and its interpretation are unlikely to be directly applicable to Australian systems. A programme of studies of non-CO2 greenhouse gas emissions from agriculture has been established that is designed to reduce uncertainty of non-CO2 greenhouse gas emissions in the Australian National Greenhouse Gas Inventory and provide outputs that will enable better on-farm management practices for reducing non-CO2 greenhouse gas emissions, particularly nitrous oxide. The systems being examined and their locations are irrigated pasture (Kyabram Victoria), irrigated cotton (Narrabri, NSW), irrigated maize (Griffith, NSW), rain-fed wheat (Rutherglen, Victoria) and rain-fed wheat (Cunderdin, WA). The field studies include treatments with and without fertilizer addition, stubble burning versus stubble retention, conventional cultivation versus direct drilling and crop rotation to determine emission factors and treatment possibilities for best management options. The data to date suggest that nitrous oxide emissions from nitrogen fertilizer, applied to irrigated dairy pastures and rain-fed winter wheat, appear much lower than the average of northern hemisphere grain and pasture studies. More variable emissions have been found in studies of irrigated cotton/vetch/wheat rotation and substantially higher emissions from irrigated maize.

Development of a high-speed sensing and detection system for automatic removal of packages with leaky seals from a high-speed food processing and packaging line

Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large amounts of money due to product recalls, consumer impact and subsequent loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and microorganisms to enter the package. In the food processing and packaging industry worldwide, there is an increasing demand for cost effective state of the art inspection technologies that are capable of reliably detecting leaky seals and delivering products at six-sigma. The new technology will develop non-destructive testing technology using digital imaging and sensing combined with a differential vacuum technique to assess seal integrity of food packages on a high-speed production line. The cost of leaky packages in Australian food industries is estimated close to AUD $35 Million per year. Contamination of packaged foods due to micro-organisms entering through air leaks can cause serious public health issues and cost companies large sums of money due to product recalls, compensation claims and loss of market share. The main source of contamination is leaks in packaging which allow air, moisture and micro-organisms to enter the package. Flexible plastic packages are widely used, and are the least expensive form of retaining the quality of the product. These packets can be used to seal, and therefore maximise, the shelf life of both dry and moist products. The seals of food packages need to be airtight so that the food content is not contaminated due to contact with microorganisms that enter as a result of air leakage. Airtight seals also extend the shelf life of packaged foods, and manufacturers attempt to prevent food products with leaky seals being sold to consumers. There are many current NDT (non-destructive testing) methods of testing the seal of flexible packages best suited to random sampling, and for laboratory purposes. The three most commonly used methods are vacuum/pressure decay, bubble test, and helium leak detection. Although these methods can detect very fine leaks, they are limited by their high processing time and are not viable in a production line. Two nondestructive in-line packaging inspection machines are currently available and are discussed in the literature review. The detailed design and development of the High-Speed Sensing and Detection System (HSDS) is the fundamental requirement of this project and the future prototype and production unit. Successful laboratory testing was completed and a methodical design procedure was needed for a successful concept. The Mechanical tests confirmed the vacuum hypothesis and seal integrity with good consistent results. Electrically, the testing also provided solid results to enable the researcher to move the project forward with a certain amount of confidence. The laboratory design testing allowed the researcher to confirm theoretical assumptions before moving into the detailed design phase. Discussion on the development of the alternative concepts in both mechanical and electrical disciplines enables the researcher to make an informed decision. Each major mechanical and electrical component is detailed through the research and design process. The design procedure methodically works through the various major functions both from a mechanical and electrical perspective. It opens up alternative ideas for the major components that although are sometimes not practical in this application, show that the researcher has exhausted all engineering and functionality thoughts. Further concepts were then designed and developed for the entire HSDS unit based on previous practice and theory. In the future, it would be envisaged that both the Prototype and Production version of the HSDS would utilise standard industry available components, manufactured and distributed locally. Future research and testing of the prototype unit could result in a successful trial unit being incorporated in a working food processing production environment. Recommendations and future works are discussed, along with options in other food processing and packaging disciplines, and other areas in the non-food processing industry.

Solder joint defects classification using the Log-Gabor Filter, the Discrete Wavelet Transform and the Discrete Cosine Transform

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure project quality and reliability. This paper proposes the use of the Log-Gabor filter bank, Discrete Wavelet Transform and Discrete Cosine Transform for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.

Controlled growth of carbon nanotubes for electronic and photovoltaic applications

Carbon nanotubes (CNTs), experimentally observed for the first time twenty years ago, have triggered an unprecedented research effort, on the account of their astonishing structural, mechanical and electronic properties. Unfortunately, the current inability in predicting the CNTs’ properties and the difficulty in controlling their position on a substrate are often limiting factors for the application of this material in actual devices. This research aims at the creation of specific methodologies for controlled synthesis of CNTs, leading to effectively employ them in various fields of electronics, e.g. photovoltaics. Focused Ion Beam (FIB) patterning of Si surfaces is here proposed as a means for ordering the assembly of vertical-aligned CNTs. With this technique, substrates with specific nano-structured morphologies have been prepared, enabling a high degree of control over CNTs’ position and size. On these nano-structured substrates, the growth of CNTs has been realized by chemical vapor deposition (CVD), i.e. thermal decomposition of hydrocarbon gases over a heated catalyst. The most common materials used as catalysts in CVD are transition metals like Fe and Ni; however, their presence in the CNT products often results in shortcomings for electronic applications, especially for those based on silicon, being the metallic impurities incompatible with very-large-scale integration (VLSI) technology. In the present work the role of Ge dots as an alternative catalysts for CNTs synthesis on Si substrates has been thoroughly assessed, finding a close connection between the catalytic activity of such material and the CVD conditions, which can affect both size and morphology of the dots. Successful CNT growths from Ge dots have been obtained by CVD at temperatures ranging from 750 to 1000°C, with mixtures of acetylene and hydrogen in an argon carrier gas. The morphology of the Si surface is observed to play a crucial role for the outcome of the CNT synthesis: natural (i.e. chemical etching) and artificial (i.e. FIB patterning, nanoindentation) means of altering this morphology in a controlled way have been then explored to optimize the CNTs yield. All the knowledge acquired in this study has been finally applied to synthesize CNTs on transparent conductive electrodes (indium-tin oxide, ITO, coated glasses), for the creation of a new class of anodes for organic photovoltaics. An accurate procedure has been established which guarantees a controlled inclusion of CNTs on ITO films, preserving their optical and electrical properties. By using this set of conditions, a CNTenhanced electrode has been built, contributing to improve the power conversion efficiency of polymeric solar cells.

Static and dynamic strain sensing using a polymer : carbon nanotube film strain sensor

The search for new multipoint, multidirectional strain sensing devices has received a new impetus since the discovery of carbon nanotubes. The excellent electrical, mechanical, and electromechanical properties of carbon nanotubes make them ideal candidates as primary materials in the design of this new generation of sensing devices. Carbon nanotube based strain sensors proposed so far include those based on individual carbon nanotubes for integration in nano or micro elecromechanical systems (NEMS/MEMS) [1], or carbon nanotube films consisting of spatially connected carbon nanotubes [2], carbon nanotube - polymer composites [3,4] for macroscale strain sensing. Carbon nanotube films have good strain sensing response and offer the possibility of multidirectional and multipoint strain sensing, but have poor performance due to weak interaction between carbon nanotubes. In addition, the carbon nanotube film sensor is extremely fragile and difficult to handle and install. We report here the static and dynamic strain sensing characteristics as well as temperature effects of a sandwich carbon nanotube - polymer sensor fabricated by infiltrating carbon nanotube films with polymer.

Mechanical considerations in fracture fixation

Bone’s capacity to repair following trauma is both unique and astounding. However, fractures sometimes fail to heal. Hence, the goal of fracture treatment is the restoration of bone’s structure, composition and function. Fracture fixation devices should provide a favourable mechanical and biological environment for healing to occur. The use of internal fixation is increasing as these devices may be applied with less invasive techniques. Recent studies suggest however that, internal fixation devices may be overly stiff and suppresses callus formation. The degree of mechanical stability influences the healing outcome. This is determined by the stiffness of the fixation device and the degree of limb loading. This project aims to characterise the fixation stability of an internal plate fixation device and the influence of modifications to its configuration on implant stability. As there are no standardised methods for the determination of fixation stiffness, the first part of this project aims to compares different methodologies and determines the most appropriate method to characterise the stiffness of internal plate fixators. The stiffness of a fixation device also influences the physiological loads experienced by the healing bone. Since bone adapts to this applied load by undergoing changes through a remodelling process, undesirable changes could occur during the period of treatment with an implant. The second part of this project aims to develop a methodology to quantify remodelling changes. This quantification is expected to aid our understanding of the changes in pattern due to implant related remodelling and on the factors driving the remodelling process. Knowledge gained in this project is useful to understand how the configuration of internal fixation devices can promote timely healing and prevent undesirable bone loss.

The effect of alcohol and drug consumption on academic performance : a treatment effect evaluation

It is often argued that consumption of alcohol, tobacco and drugs is detrimental to the cognitive abilities of teenagers. In order to disentangle a possible causal effect of these substances use from a self-selection bias, we control for pupils previous performance and for their previous rate of progression applying a DiDiD strategy. Using the NELS 1988 panel dataset, we find that the effects of alcohol and tobacco on test scores disappear once the selection bias is controlled for (this does not preclude long term detrimental effects). However, we find reliable evidence that heavy use of drugs (marijuana and cocaine) has direct detrimental effects on educational achievements. Hence, our results may have significant policy implications.

Lignocellulosics as a renewable feedstock for chemical industry : chemical hydrolysis and pretreatment processes

Lignocellulosic materials including agricultural, municipal and forestry residues, and dedicated bioenergy crops offer significant potential as a renewable feedstock for the production of fuels and chemicals. These products can be chemically or functionally equivalent to existing products that are produced from fossil-based feedstocks. To unlock the potential of lignocellulosic materials, it is necessary to pretreat or fractionate the biomass to make it amenable to downstream processing. This chapter explores current and developing technologies for the pretreatment and fractionation of lignocellulosic biomass for the production of chemicals and fuels.

Numerical Modelling of Mechanical Behaviour of Graphene

Graphene, one of the allotropes (diamond, carbon nanotube, and fullerene) of element carbon, is a monolayer of honeycomb lattice of carbon atoms, which was discovered in 2004. The Nobel Prize in Physics 2010 was awarded to Andre Geim and Konstantin Novoselov for their ground breaking work on the two-dimensional (2D) graphene [1]. Since its discovery, the research communities have shown a lot of interest in this novel material owing to its intriguing electrical, mechanical and thermal properties. It has been confirmed that grapheme possesses very peculiar electrical properties such as anomalous quantum hall effect, and high electron mobility at room temperature (250000 cm2/Vs). Graphene also has exceptional mechanical properties. It is one of the stiffest (modulus ~1 TPa) and strongest (strength ~100 GPa) materials. In addition, it has exceptional thermal conductivity (5000 Wm-1K-1). Due to these exceptional properties, graphene has demonstrated its potential for broad applications in micro and nano devices, various sensors, electrodes, solar cells and energy storage devices and nanocomposites. In particular, the excellent mechanical properties of graphene make it more attractive for development next generation nanocomposites and hybrid materials...