998 resultados para Unstable conditions


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Today, Australian agriculture is not where we hoped it would be. Despite being highly productive and the nation's only 'strongly competitive industry', it is struggling across the country. There are successes, as there always will be, but the bulk of our food and fibre production is from enterprises with minimal profitability and unstable or unsound finances. A debt-deflation spiral and subprime mortgage crisis are now being fuelled by property fire sales while leading bankers proclaim no problem and governments dance at the edges. However, it is not just the bush that has problems. National economic conditions are deteriorating with per capita incomes falling and real interest rates still high. Well-informed policy strategies and effective responses are needed quickly if Australians are to avoid needless losses of capacity and wealth destruction in the cities and the bush.

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Acid sulfate soils (ASS) is a stress factor that is responsible for the failure of some mangrove restoration projects, including abandoned aquaculture ponds converted from mangrove ecosystems. Through experimental and field studies, this research provides a better understanding of the biogeochemistry of ASS disturbance and the response of mangrove seedlings (Rhizophoraceae) under high metal levels and acidic conditions. This study found that mangrove restorations under ASS disturbance can work but with lower numbers of survived seedlings. To prevent toxicity under high levels of metal, seedlings retained metals in their roots and sparingly distributed them into aerial parts with low mobility. The presence of high levels of potential acidity parameters would allow pyrite to oxidise, thus increasing metal levels and acidity, which in turn affected the survival and growth of the seedlings.

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Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

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This research aims to explore and identify political risks on a large infrastructure project in an exaggerated environment to ascertain whether sufficient objective information can be gathered by project managers to utilise risk modelling techniques. During the study, the author proposes a new definition of political risk; performs a detailed project study of the Neelum Jhelum Hydroelectric Project in Pakistan; implements a probabilistic model using the principle of decomposition and Bayes probabilistic theorem and answers the question: was it possible for project managers to obtain all the relevant objective data to implement a probabilistic model?

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Aim Large-scale patterns linking energy availability, biological productivity and diversity form a central focus of ecology. Despite evidence that the activity and abundance of animals may be limited by climatic variables associated with regional biological productivity (e.g. mean annual precipitation and annual actual evapotranspiration), it is unclear whether plant–granivore interactions are themselves influenced by these climatic factors across broad spatial extents. We evaluated whether climatic conditions that are known to alter the abundance and activity of granivorous animals also affect rates of seed removal. Location Eleven sites across temperate North America. Methods We used a common protocol to assess the removal of the same seed species (Avena sativa) over a 2-day period. Model selection via the Akaike information criterion was used to determine a set of candidate binomial generalized linear mixed models that evaluated the relationship between local climatic data and post-dispersal seed predation. Results Annual actual evapotranspiration was the single best predictor of the proportion of seeds removed. Annual actual evapotranspiration and mean annual precipitation were both positively related to mean seed removal and were included in four and three of the top five models, respectively. Annual temperature range was also positively related to seed removal and was an explanatory variable in three of the top four models. Main conclusions Our work provides the first evidence that energy and precipitation, which are known to affect consumer abundance and activity, also translate to strong, predictable patterns of seed predation across a continent. More generally, these findings suggest that future changes in temperature and precipitation could have widespread consequences for plant species composition in grasslands, through impacts on plant recruitment.

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Purpose To determine the prescribed drug-utilisation pattern for six common chronic conditions in adult South Africans in a cross-sectional survey. Methods 13 826 randomly selected participants, 15 years and older, were surveyed by trained fieldworkers at their homes in 1998. Questionnaires included socio-demographic, chronic-disease and drug-use data. The prescribed drugs were recorded from participants' medication containers. The Anatomical Therapeutic Classification (ATC) code of the drugs for tuberculosis (TB), diabetes, hypertension, hyperlipidaemia, other atherosclerosis-related conditions, such as heart conditions or cerebrovascular accidents (CVA), and asthma or chronic obstructive pulmonary disease (COPD), was recorded. The use of logistic regression analyses identified the determinants of those patients who used prescription medication for these six conditions. Results 18.4% of the women and 12.5% of the men used drugs for the six chronic conditions. Men used drugs most frequently for hypertension (50.9%) and asthma or chronic bronchitis (24.3%), while in women it was for hypertension (59.9%) and diabetes (17.5%). The logistic regression analyses showed that women, wealthier and older people, and those with medical insurance used these chronic-disease drugs more frequently compared to men, younger or poor people, or those without medical insurance. The African population group used these drugs less frequently than any other ethnic group. The inappropriate use of methyldopa was found for 14.8% of all antihypertensive drugs, while very few people used aspirin. Conclusions The methodology of this study provides a means of ascertaining the chronic-disease drug-utilisation pattern in national health surveys. The pattern described, suggests an inequitable use of chronic-disease drugs and inadequate use of some effective drugs to control the burden of chronic diseases in South Africa. Copyright © 2004 John Wiley & Sons, Ltd.

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Synthesis of imines from amines and aliphatic alcohols (C1–C6) in the presence of base on supported palladium nanoparticles has been achieved for the first time. The catalytic system shows high activity and selectivity in open air at room temperature. As an example of the isostructural Ln3Sb3Co2O14 (Ln: La, Pr, Nd, Sm—Ho) series with an ordered pyrochlore structure, the La variant is prepared by a citrate complex method employing stoichiometric amounts of La(NO3)3, Co(NO3)2, and Sb tartrate together with citric acid with a metal/citrate molar ratio of 1:2

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Objective: To estimate the relative inpatient costs of hospital-acquired conditions. Methods: Patient level costs were estimated using computerized costing systems that log individual utilization of inpatient services and apply sophisticated cost estimates from the hospital's general ledger. Occurrence of hospital-acquired conditions was identified using an Australian ‘condition-onset' flag for diagnoses not present on admission. These were grouped to yield a comprehensive set of 144 categories of hospital-acquired conditions to summarize data coded with ICD-10. Standard linear regression techniques were used to identify the independent contribution of hospital-acquired conditions to costs, taking into account the case-mix of a sample of acute inpatients (n = 1,699,997) treated in Australian public hospitals in Victoria (2005/06) and Queensland (2006/07). Results: The most costly types of complications were post-procedure endocrine/metabolic disorders, adding AU$21,827 to the cost of an episode, followed by MRSA (AU$19,881) and enterocolitis due to Clostridium difficile (AU$19,743). Aggregate costs to the system, however, were highest for septicaemia (AU$41.4 million), complications of cardiac and vascular implants other than septicaemia (AU$28.7 million), acute lower respiratory infections, including influenza and pneumonia (AU$27.8 million) and UTI (AU$24.7 million). Hospital-acquired complications are estimated to add 17.3% to treatment costs in this sample. Conclusions: Patient safety efforts frequently focus on dramatic but rare complications with very serious patient harm. Previous studies of the costs of adverse events have provided information on ‘indicators’ of safety problems rather than the full range of hospital-acquired conditions. Adding a cost dimension to priority-setting could result in changes to the focus of patient safety programmes and research. Financial information should be combined with information on patient outcomes to allow for cost-utility evaluation of future interventions.

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This paper examines the issue of face, speaker and bi-modal authentication in mobile environments when there is significant condition mismatch. We introduce this mismatch by enrolling client models on high quality biometric samples obtained on a laptop computer and authenticating them on lower quality biometric samples acquired with a mobile phone. To perform these experiments we develop three novel authentication protocols for the large publicly available MOBIO database. We evaluate state-of-the-art face, speaker and bi-modal authentication techniques and show that inter-session variability modelling using Gaussian mixture models provides a consistently robust system for face, speaker and bi-modal authentication. It is also shown that multi-algorithm fusion provides a consistent performance improvement for face, speaker and bi-modal authentication. Using this bi-modal multi-algorithm system we derive a state-of-the-art authentication system that obtains a half total error rate of 6.3% and 1.9% for Female and Male trials, respectively.

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Fire safety design of buildings is essential to safeguard lives and minimize the loss of damage to properties. Light-weight cold-formed steel channel sections along with fire resistive plasterboards are used to construct light gauge steel frame floor systems to provide the required fire resistance rating. However, simply adding more plasterboard layers is not an efficient method to increase FRR. Hence this research focuses on using joists with improved joist section profiles such as hollow flange sections to increase the structural capacity of floor systems under fire conditions and thus their FRR. In this research, the structural and thermal behaviour of LSF floor systems made of LiteSteel Beams with different plasterboard and insulation configurations was investigated using four full scale tests under standard fires. Based on the ultimate failure load of the floor joist at ambient temperature, transient state fire tests were conducted for different Load Ratios. These fire tests showed that the new LSF floor system has improved the FRR well above that of those made of lipped channel sections. The joist failure was predominantly due to local buckling of LSB compression flanges near mid-span with severe yielding of tension flanges. Fire tests have provided valuable structural and thermal performance data of tested floor systems that included time-temperature profiles, and failure times and temperatures. Average failure temperatures of LSB joists and reduced yield strengths were used to predict their ultimate moment capacities, which were compared with corresponding test capacities. This allowed an assessment in relation to the accuracy of current design rules for steel joists at elevated temperatures. This paper presents the details of full scale fire tests of LSF floor systems made of LSB joists with different plasterboard and insulation configurations and their results along with some important findings.

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GVHD remains the major complication of allo-HSCT. Murine models are the primary system used to understand GVHD, and to develop potential therapies. Several factors are critical for GVHD in these models; including histo- compatibility, conditioning regimen, and T-cell number. We serendipitously found that environmental factors such as the caging system and bedding also significantly impact the kinetics of GVHD in these models. This is important because such factors may influence the experimental conditions required to cause GVHD and how mice respond to various treatments. Consequently, this is likely to alter interpretation of results between research groups, and the perceived effectiveness of experimental therapies.

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This research quantifies traffic congestion and travel time reliability with case study on a major arterial road in Brisbane. The focus is on the analysis of impact of incidents (e.g., road accidents) on travel time reliability. Real traffic (Bluetooth) and incident records from Coronation Drive, Brisbane are utilized for the study. The findings include significant impact of incidents on traffic congestion and travel time reliability. The knowledge gained is useful in various applications such as traveler information systems, and cost-benefit analysis of various strategies to reduce the traffic incidents and its' impacts.

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Pilot and industrial scale dilute acid pretreatment data can be difficult to obtain due to the significant infrastructure investment required. Consequently, models of dilute acid pretreatment by necessity use laboratory scale data to determine kinetic parameters and make predictions about optimal pretreatment conditions at larger scales. In order for these recommendations to be meaningful, the ability of laboratory scale models to predict pilot and industrial scale yields must be investigated. A mathematical model of the dilute acid pretreatment of sugarcane bagasse has previously been developed by the authors. This model was able to successfully reproduce the experimental yields of xylose and short chain xylooligomers obtained at the laboratory scale. In this paper, the ability of the model to reproduce pilot scale yield and composition data is examined. It was found that in general the model over predicted the pilot scale reactor yields by a significant margin. Models that appear very promising at the laboratory scale may have limitations when predicting yields on a pilot or industrial scale. It is difficult to comment whether there are any consistent trends in optimal operating conditions between reactor scale and laboratory scale hydrolysis due to the limited reactor datasets available. Further investigation is needed to determine whether the model has some efficacy when the kinetic parameters are re-evaluated by parameter fitting to reactor scale data, however, this requires the compilation of larger datasets. Alternatively, laboratory scale mathematical models may have enhanced utility for predicting larger scale reactor performance if bulk mass transport and fluid flow considerations are incorporated into the fibre scale equations. This work reinforces the need for appropriate attention to be paid to pilot scale experimental development when moving from laboratory to pilot and industrial scales for new technologies.