927 resultados para Roundup Ready corn
Resumo:
As all environmental problems are caused by human systems of design, sustainability can be seen as a design problem. Given the massive energy and material flows through the built environment, sustainability simply cannot be achieved without the re-design of our urban areas. ‘Eco-retrofitting’, as used here, means modifying buildings and/or urban areas to create net positive social and environmental impacts – both on site and off site. While this has probably not been achieved anywhere as yet, myriad but untapped eco-solutions are already available which could be up-scaled to the urban level. It is now well established that eco-retrofitting buildings and cities with appropriate design technology can pay for itself through lower health costs, productivity increases and resource savings. Good design would also mean happier human and ecological communities at a much lower cost over time. In fact, good design could increase life quality and the life support services of nature while creating sustainable‘economic’growth. The impediments are largely institutional and intellectual, which can be encapsulated in the term ‘managerial’. There are, however, also systems design solutions to the managerial obstacles that seem to be stalling the transition to sustainable systems designs. Given the sustainability imperative, then, why is the adoption of better management systems so slow? The oral presentation will show examples of ways in which built environment design can create environments that not only reduce the ongoing damage of past design, but could theoretically generate net positive social and ecological outcomes over their life cycle. These illustrations show that eco-retrofitting could cost society less than doing nothing - especially given the ongoing renovations of buildings - but for managerial hurdles. The paper outlines on how traditional managerial approaches stand in the way of ‘design for ecosystem services’, and list some management solutions that have long been identified, but are not yet widely adopted. Given the pervasive nature of these impediments and their alternatives, they are presented by way of examples. A sampling of eco-retrofitting solutions are also listed to show that ecoretrofitting is a win-win-win solution that stands ready to be implemented by people having management skills and/or positions of influence.
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Excessive consumption of alcohol is a serious public health problem. While intensive treatments are suitable for those who are physically dependent on alcohol, they are not cost-effective options for the vast majority of problem drinkers who are not dependent. There is good evidence that brief interventions are effective in reducing overall alcohol consumption, alcohol-related problems, and health-care utilisation among nondependent problem drinkers. Psychologists are in an ideal position to opportunistically detect people who drink excessively and to offer them brief advice to reduce their drinking. In this paper we outline the process involved in providing brief opportunistic screening and intervention for problem drinkers. We also discuss methods that psychologists can employ if a client is not ready to reduce drinking, or is ambivalent about change. Depending on the client's level of motivation to change, psychologists can engage in either an education-clarification approach, a commitment-enhancement approach, or a skills-training approach. Routine engagement in opportunistic intervention is an important public-health approach to reducing alcohol-related harm in the community.
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The present study was conducted to explore the potential to incorporate local plant-based feed ingredients into diets formulated for the mud crab species, Scylla paramamosain, commonly exploited for aquaculture in South-east Asia. Four test ingredients (defatted soybean meal, rice bran, cassava meal and corn flour) were incorporated at 30% or 45% inclusion levels in a fishmeal-based reference diet and used in digestibility trials where apparent digestibility coefficients (ADCs) for experimental diets and test ingredients were determined. Generally, high ADC values were obtained using diets containing 30% soybean meal or rice bran. By contrast, the lowest ADC values were obtained for the diet containing 45% cassava meal [70.9% for dry matter (ADMD); 77.1% for crude protein (ACPD) and 80.2% for gross energy (AGED)]. Similar trends were observed when ADC ingredient (I) digestibilities were compared. Specifically, the highest ADCI values were obtained for soybean meal when used at a 30% inclusion level (87.6% ADMDI; 98.4% ACPDI and 95.6% AGEDI) while the lowest ADCI values were obtained using cassava meal at a 45% inclusion level (53.8% ADMDI; 60.2% ACPDI and 67.3% AGEDI). Based on the current findings, we propose that soybean meal and rice bran could be considered for incorporation into formulated diets for S. paramamosain.
Resumo:
The present study examined the capacity of the mud crab, Scylla serrata to digest experimental diets that contained different animal and plant-based feed meals or different levels or types of starch. The apparent dry matter digestibility (ADMD) coefficients for all feed meals tested in the first part of this study, except meat meal, were similar (78–88%). Crude protein digestibility (ACPD) coefficients for all feed meals were relatively high, with values ranging from 86% to 96%. Cotton seed meal, poultry meal, canola meal, fishmeal, soybean meal and lupin meal had similar gross energy digestibility (AGED) values (P>0.05) ranging from 84% to 89%. In the second part of this study, the impact of selected starches on the digestibility of fishmeal-based formulated diets was assessed. The apparent starch digestibility (ASD) of wheat starch decreased significantly as the inclusion level was increased from 15% to 60%, however, there was no significant effect on ACPD values. At a 30% inclusion level, the ASD of diets containing different starches decreased in the order corn>wheat>potato=rice. Moreover, ACPD values were significantly higher (P<0.05) in the diets containing corn or rice starch than in those containing wheat or potato starches.
Resumo:
In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality.
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Knowledge intensive services are the fastest growing segment of the international economy and the digital creative industries are a key segment therein. Australia is well positioned to exploit this opportunity but has a skills shortage in the digital content industries in terms of commercial ready graduates. We report on a solution to this problem, in the form of an online creative community of practice – www.60Sox.org - where new graduates are mentored by Australian industry leaders - the 2bobmob. We describe this community of practice as a virtual creative ecology and discuss networks, peer feedback and mentoring as key elements of post-tertiary learning, in the context of portfolio career progression.
Resumo:
The ready availability of suitably zoned and serviced land is one of the key factors in the timely and cost effective provision of new land for development. Unfortunately, in many high population growth areas, land that may be available does not have ready access to infrastructure, or the appropriate designation/s (zoning) in place. The corresponding lag in supply frequently bears the blame for the resultant disequilibrium in the market and affordability pressures on the end product. Government has the capacity to respond to the issue of land supply in a number of ways. Proactive measures define longer term goals and set the ground rules moving forwards. Reactive policy decisions are made in an often hostile environment where stakeholder interests conflict. With a trend to increased regulation, government risks further constraining the viability of land development in high growth areas, without full consideration of all the supply side variables. This preliminary paper will identify a number of the variables which may be constraining the supply of land for residential development in South East Queensland given the current regulatory environment. It will examine the interrelationship between these supply side constraints, a full understanding of which is required by government in order for its policies to stimulate, rather than restrict the supply of land in this high growth region.
Resumo:
An Asset Management (AM) life-cycle constitutes a set of processes that align with the development, operation and maintenance of assets, in order to meet the desired requirements and objectives of the stake holders of the business. The scope of AM is often broad within an organization due to the interactions between its internal elements such as human resources, finance, technology, engineering operation, information technology and management, as well as external elements such as governance and environment. Due to the complexity of the AM processes, it has been proposed that in order to optimize asset management activities, process modelling initiatives should be adopted. Although organisations adopt AM principles and carry out AM initiatives, most do not document or model their AM processes, let alone enacting their processes (semi-) automatically using a computer-supported system. There is currently a lack of knowledge describing how to model AM processes through a methodical and suitable manner so that the processes are streamlines and optimized and are ready for deployment in a computerised way. This research aims to overcome this deficiency by developing an approach that will aid organisations in constructing AM process models quickly and systematically whilst using the most appropriate techniques, such as workflow technology. Currently, there is a wealth of information within the individual domains of AM and workflow. Both fields are gaining significant popularity in many industries thus fuelling the need for research in exploring the possible benefits of their cross-disciplinary applications. This research is thus inspired to investigate these two domains to exploit the application of workflow to modelling and execution of AM processes. Specifically, it will investigate appropriate methodologies in applying workflow techniques to AM frameworks. One of the benefits of applying workflow models to AM processes is to adapt and enable both ad-hoc and evolutionary changes over time. In addition, this can automate an AM process as well as to support the coordination and collaboration of people that are involved in carrying out the process. A workflow management system (WFMS) can be used to support the design and enactment (i.e. execution) of processes and cope with changes that occur to the process during the enactment. So far few literatures can be found in documenting a systematic approach to modelling the characteristics of AM processes. In order to obtain a workflow model for AM processes commonalities and differences between different AM processes need to be identified. This is the fundamental step in developing a conscientious workflow model for AM processes. Therefore, the first stage of this research focuses on identifying the characteristics of AM processes, especially AM decision making processes. The second stage is to review a number of contemporary workflow techniques and choose a suitable technique for application to AM decision making processes. The third stage is to develop an intermediate ameliorated AM decision process definition that improves the current process description and is ready for modelling using the workflow language selected in the previous stage. All these lead to the fourth stage where a workflow model for an AM decision making process is developed. The process model is then deployed (semi-) automatically in a state-of-the-art WFMS demonstrating the benefits of applying workflow technology to the domain of AM. Given that the information in the AM decision making process is captured at an abstract level within the scope of this work, the deployed process model can be used as an executable guideline for carrying out an AM decision process in practice. Moreover, it can be used as a vanilla system that, once being incorporated with rich information from a specific AM decision making process (e.g. in the case of a building construction or a power plant maintenance), is able to support the automation of such a process in a more elaborated way.
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Nitrous oxide (N2O) is a potent agricultural greenhouse gas (GHG). More than 50% of the global anthropogenic N2O flux is attributable to emissions from soil, primarily due to large fertilizer nitrogen (N) applications to corn and other non-leguminous crops. Quantification of the trade–offs between N2O emissions, fertilizer N rate, and crop yield is an essential requirement for informing management strategies aiming to reduce the agricultural sector GHG burden, without compromising productivity and producer livelihood. There is currently great interest in developing and implementing agricultural GHG reduction offset projects for inclusion within carbon offset markets. Nitrous oxide, with a global warming potential (GWP) of 298, is a major target for these endeavours due to the high payback associated with its emission prevention. In this paper we use robust quantitative relationships between fertilizer N rate and N2O emissions, along with a recently developed approach for determining economically profitable N rates for optimized crop yield, to propose a simple, transparent, and robust N2O emission reduction protocol (NERP) for generating agricultural GHG emission reduction credits. This NERP has the advantage of providing an economic and environmental incentive for producers and other stakeholders, necessary requirements in the implementation of agricultural offset projects.
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Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance
Resumo:
Despite some segments of the creative industries in Australia performing better than other segments in terms of earnings and employment growth, they all rely on highly skilled workers and face similar workforce challenges. Workers typically experience multiple entry attempts, spells of unemployment, short-term contracts, high degrees of mobility, casual/part-time employment within and outside the creative industries, and pressure to ensure their skills remain relevant. Skills shortages and gaps, an insufficient supply of high quality industry-ready graduates, difficulties in predicting demand for skills, weak linkages between industry and education providers, reliance on overseas talent in some segments, limited opportunities for workers to engage in skill development, and pressure on workers to keep abreast of technological developments are ongoing issues in the creative industries workforce. In response to these concerns, the Australian Research Council, three State Governments, industry, and a large vocational education and training (VET) provider funded Queensland University of Technology (QUT) to conduct the 60Sox project. This three-year project investigated the education, training, and work experiences of aspiring creatives defined as new entrants, recent graduates, and students enrolled in creative industries courses. It involved the largest survey of aspiring creatives ever undertaken in Australia, attracting 507 respondents, and a survey of 50 employers. Using the framework proposed by Hannan, Raffe, and Smyth (1996), this article presents findings from an analysis of the macro and micro labour market outcomes of aspiring creatives using data from the two 60Sox project surveys and publicly available sources. The analysis confirmed that many graduates of creative industries courses who participated in the 60Sox survey and the national surveys for the National Centre for Vocational Education Research and Graduate Careers Australia were struggling to make a successful transition from education to work. This article also discusses the causes of this key finding and possible solutions to address transition issues.
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User needs and wants dictate the way in which products are designed, produced, used and disposed of. Western society in particular has become very consumer driven and the waste resulting from such activity has the potential to be disastrous. The creation of emotional attachment with possessions is one way of approaching sustainable consumer-product relationships. The aim of this research was to gain a deeper understanding of the interaction and emotional attachment that consumers have and develop with their products. It outlines literature relating to consumer emotion and experience in relation to products, and how pleasurable product user relationships can be prolonged. It is evident from the literature that the roles of materials in the emotional attachment consumers have with products needed to be further explored. A study was conducted to determine consumers. concepts of six materials currently used in product design. This involved participants being given a Concept Prompt Probe with textual prompts to assist in discussion about the materials in question. The discussions between the 15 participant groups of two people, one male and one female, were then transcribed and coded ready for analysis. The study findings demonstrate consumers. concepts of the six materials. The findings show both physical and emotional consumer concepts of the materials. It is, however, the interaction of these concepts that is the most significant finding of this research. Each material concept is not only judged emotionally by consumers in its own right but in relation to other concepts as well. The interaction of the consumers. concepts of materials can considerably effect the emotional judgement made about the material and the appropriateness of its application. This research makes a significant contribution to knowledge regarding the effect materials have on the consumers by identifying how materials can prompt emotional judgements and thereby alter the product user experience.
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In the Knowledge Society, new demands are placed on teachers as they strive to empower young people to be global citizens, ready for the 21st century. Systemic shifts need to be made, however, to build capacity across the workforce to practise new ways of teaching and learning, including the personalisation of teacher professional development. This article argues new strategies and approaches for effective adult learning, including an individualised focus, context-based learning and an empowerment of teachers to develop their own personal learning networks. This article concludes with an analysis of the challenges facing professional development leaders in moving towards personalised teacher learning.
Resumo:
The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.
Resumo:
Reflective practice is widely considered across discussions around educational psychology, professional identity, employability of graduates, and generic or graduate capabilities. Critical reflection is essential for providing a bridge between the university and the workplace, and for ultimately preparing work ready graduates (Patrick et al, 2008). Work integrated learning, particularly through internships and work placements for students, is viewed as a valuable approach for students developing skills in reflective practice. Reflective journals are one of the tools often used to encourage and develop student reflection. Shifting the reflective journal to an online interface as a reflective blog presents opportunities for more meaningful, frequent and richer interaction between the key players in a work integrated learning experience. This paper examines the adoption, implementation and refinement of the use of reflective blogs in a work integrated learning unit for business students majoring in advertising, marketing and public relations disciplines. The reflective blog is discussed as a learning and assessment tool, including the approaches taken to integrate and scaffold the blog as part of the work integrated learning experience. Graduate capabilities were used as cornerstones for students to frame students’ thinking, experiences and reflection. These capabilities emphasise the value of coherent theoretical and practical knowledge, coupled with critical, creative and analytical thinking, problem solving skills, self reliance and resilience. Underlying these graduate capabilities is a focus on assessment for learning matched with assessment of learning. Using specific triggers and prompts as part of the reflective process, and incorporating ongoing feedback from academic supervisors, students moved from descriptive levels of reflection, to more meaningful and critical reflection. Students’ blogs are analysed to identify key themes, challenges and achievements in the work integrated learning experience. Suggestions for further development and improvement, together with a model of best practice, are proposed.