23 resultados para Combermere, Stapleton Cotton, 1st viscount, 1773-1865.

em Queensland University of Technology - ePrints Archive


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The first Workshop on Service-Oriented Business Networks and Ecosystems (SOBNE ’09) is held in conjunction with the 13th IEEE International EDOC Conference on 2 September 2009 in Auckland, New Zealand. The SOBNE ’09 program includes 9 peer-reviewed papers (7 full and 2 short papers) and an open discussion session. This introduction to the Proceedings of SOBNE ’09 starts with a brief background of the motivation for the workshop. Next, it contains a short description of the peer-reviewed papers, and finally, after some concluding statements and the announcement of the winners of the Best Reviewer Award and the Most Promising Research Award, it lists the members of the SOBNE ’09 Program Committee and external reviewers of the workshop submissions.

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Our students come from diverse backgrounds. They need flexibility in their learning, and opportunities to review aspects of curriculum they are less confident with. An online teaching and learning programme called the Histology Challenge has been developed to supplement learning experiences offered in several first year anatomy and anatomy & physiology units at QUT. The programme is designed to be integrated with the existing Blackboard sites. The Histology Challenge emphasises the foundation concept that a complex system, such as the human body, can be better understood by examining its simpler components. The tutorial allows students to examine the cells and tissues which ultimately determine structural and functional properties of body organs. The program is interactive, asking students to make decisions and choices, demonstrating an integrated understanding of systemic and cellular aspects. It provides users with the ability to progress at their own pace and to test their understanding and knowledge. For the developer the learning activity can be easily controlled and modified via the use of text files. There are several key elements of this programme, designed to promote specific aspects of student learning. Minimum text is used, instead there is a strong emphasis on instructive artwork and original, high quality histology images presented within a framework that reinforces learning and promotes problem solving skills.

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The middle years of schooling are increasingly recognised as a crucial stage in students' lives, one that has significant consequences for ongoing educational success. International research indicates that young adolescents benefit from programs designed especially for their needs, and the middle years have become an important reform issue for education systems. Teaching Middle Years offers a systematic overview of the philosophy, principles and issues in middle schooling. It includes contributions from academics and school-based practitioners on intellectual and emotional development in early adolescence, pedagogy, curriculum and assessment of middle years students. Written for teachers, student teachers, education leaders and policy makers, Teaching Middle Years is an essential resource for anyone involved in educating young adolescents. Teaching Middle Years is the first comprehensive Australian book to match and surpass the quality of many overseas publications.'

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An automated gas sampling methodology has been used to estimate nitrous oxide (N2O) emissions from heavy black clay soil in northern Australia where split applications of urea were applied to furrow irrigated cotton. Nitrous oxide emissions from the beds were 643 g N/ha over the 188 day measurement period (after planting), whilst the N2O emissions from the furrows were significantly higher at 967 g N/ha. The DNDC model was used to develop a full season simulation of N2O and N2 emissions. Seasonal N2O emissions were equivalent to 0.83% of applied N, with total gaseous N losses (excluding NH3) estimated to be 16% of the applied N.

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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.

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Cotton is one of the most important irrigated crops in subtropical Australia. In recent years, cotton production has been severely affected by the worst drought in recorded history, with the 2007–08 growing season recording the lowest average cotton yield in 30 years. The use of a crop simulation model to simulate the long-term temporal distribution of cotton yields under different levels of irrigation and the marginal value for each unit of water applied is important in determining the economic feasibility of current irrigation practices. The objectives of this study were to: (i) evaluate the CROPGRO-Cotton simulation model for studying crop growth under deficit irrigation scenarios across ten locations in New South Wales (NSW) and Queensland (Qld); (ii) evaluate agronomic and economic responses to water inputs across the ten locations; and (iii) determine the economically optimal irrigation level. The CROPGRO-Cotton simulation model was evaluated using 2 years of experimental data collected at Kingsthorpe, Qld. The model was further evaluated using data from nine locations between northern NSW and southern Qld. Long-term simulations were based on the prevalent furrowirrigation practice of refilling the soil profile when the plant -available soil water content is<50%. The model closely estimated lint yield for all locations evaluated. Our results showed that the amounts of water needed to maximise profit and maximise yield are different, which has economic and environmental implications. Irrigation needed to maximise profits varied with both agronomic and economic factors, which can be quite variable with season and location. Therefore, better tools and information that consider the agronomic and economic implications of irrigation decisions need to be developed and made available to growers.

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Irrigation is known to stimulate soil microbial carbon and nitrogen turnover and potentially the emissions of nitrous oxide (N2O) and carbon dioxide (CO2). We conducted a study to evaluate the effect of three different irrigation intensities on soil N2O and CO2 fluxes and to determine if irrigation management can be used to mitigate N2O emissions from irrigated cotton on black vertisols in South-Eastern Queensland, Australia. Fluxes were measured over the entire 2009/2010 cotton growing season with a fully automated chamber system that measured emissions on a sub-daily basis. Irrigation intensity had a significant effect on CO2 emission. More frequent irrigation stimulated soil respiration and seasonal CO2 fluxes ranged from 2.7 to 4.1 Mg-C ha−1 for the treatments with the lowest and highest irrigation frequency, respectively. N2O emission happened episodic with highest emissions when heavy rainfall or irrigation coincided with elevated soil mineral N levels and seasonal emissions ranged from 0.80 to 1.07 kg N2O-N ha−1 for the different treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the cotton cropping season, uncorrected for background emissions, ranged from 0.40 to 0.53 % of total N applied for the different treatments. There was no significant effect of the different irrigation treatments on soil N2O fluxes because highest emission happened in all treatments following heavy rainfall caused by a series of summer thunderstorms which overrode the effect of the irrigation treatment. However, higher irrigation intensity increased the cotton yield and therefore reduced the N2O intensity (N2O emission per lint yield) of this cropping system. Our data suggest that there is only limited scope to reduce absolute N2O emissions by different irrigation intensities in irrigated cotton systems with summer dominated rainfall. However, the significant impact of the irrigation treatments on the N2O intensity clearly shows that irrigation can easily be used to optimize the N2O intensity of such a system.

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Cotton growing landscapes in Australia have been dominated by dual-toxin transgenic Bt varieties since 2004. The cotton crop has thus effectively become a sink for the main target pest, Helicoverpa armigera. Theory predicts that there should be strong selection on female moths to avoid laying on such plants. We assessed oviposition, collected from two cotton-growing regions, by female moths when given a choice of tobacco, cotton and cabbage. Earlier work in the 1980s and 1990s on populations from the same geographic locations indicated these hosts were on average ranked as high, mid and low preference plants, respectively, and that host rankings had a heritable component. In the present study, we found no change in the relative ranking of hosts by females, with most eggs being laid on tobacco, then cotton and least on cabbage. As in earlier work, some females laid most eggs on cotton and aspects of oviposition behaviour had a heritable component. Certainly, cotton is not avoided as a host, and the implications of these finding for managing resistance to Bt cotton are discussed.

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"The music industry is going through a period of immense change brought about in part by the digital revolution. What is the role of music in the age of computers and the internet? How has the music industry been transformed by the economic and technological upheavals of recent years, and how is it likely to change in the future? This is the first major study of the music industry in the new millennium. Wikström provides an international overview of the music industry and its future prospects in the world of global entertainment. He illuminates the workings of the music industry, and captures the dynamics at work in the production of musical culture between the transnational media conglomerates, the independent music companies and the public." -- back cover Table of Contents Introduction: Music in the Cloud Chapter 1: A Copyright Industry. Chapter 2: Inside the Music Industry Chapter 3: Music and the Media Chapter 4: Making Music - An Industrial or Creative Process Chapter 5: The Social and Creative Music Fan Chapter 6: Future Sounds

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The cotton strip assay (CSA) is an established technique for measuring soil microbial activity. The technique involves burying cotton strips and measuring their tensile strength after a certain time. This gives a measure of the rotting rate, R, of the cotton strips. R is then a measure of soil microbial activity. This paper examines properties of the technique and indicates how the assay can be optimised. Humidity conditioning of the cotton strips before measuring their tensile strength reduced the within and between day variance and enabled the distribution of the tensile strength measurements to approximate normality. The test data came from a three-way factorial experiment (two soils, two temperatures, three moisture levels). The cotton strips were buried in the soil for intervals of time ranging up to 6 weeks. This enabled the rate of loss of cotton tensile strength with time to be studied under a range of conditions. An inverse cubic model accounted for greater than 90% of the total variation within each treatment combination. This offers support for summarising the decomposition process by a single parameter R. The approximate variance of the decomposition rate was estimated from a function incorporating the variance of tensile strength and the differential of the function for the rate of decomposition, R, with respect to tensile strength. This variance function has a minimum when the measured strength is approximately 2/3 that of the original strength. The estimates of R are almost unbiased and relatively robust against the cotton strips being left in the soil for more or less than the optimal time. We conclude that the rotting rate X should be measured using the inverse cubic equation, and that the cotton strips should be left in the soil until their strength has been reduced to about 2/3.