978 resultados para CLASTIC INPUTS
Resumo:
Trace element concentrations and combined Sr- and Nd-isotope compositions were determined on stromatolitic carbonates (microbialites) from the 2.52 Ga Campbellrand carbonate platform (South Africa). Shale-normalised rare earth element and yttrium patterns of the ancient samples are similar to those of modern seawater in having positive La and Y anomalies and in being depleted in light rare earth elements. In contrast to modem seawater (and microbialite proxies), the 2.52 Ga samples lack a negative Ce anomaly but possess a positive Eu anomaly. These latter trace element characteristics are interpreted to reflect anoxic deep ocean waters where, unlike today, hydrothermal Fe input was not oxidised, and scavenged and rare earth elements were not coprecipitated with Fe-oxyhydroxides. The persistence of a positive Eu anomaly in relatively shallow Campbellrand platform waters indicates a dramatic reversal from hydrothermally dominated (Archaean) to continental erosion-dominated (Phanerozoic) rare earth element flux ratio. The dominant hydrothermal input is also expressed in the initial Sr- and Nd-isotope ratios. There is collinear variation in Sr-Nd systematics, which range from primitive values (Sr-87/Sr-86 of 0.702386 and epsilon (Nd) of +2.1) to more evolved crustal ratios. Mixing calculations show that the range in trace element ratios (e.g., Y/Ho) and initial isotope ratios is not a result of contamination by trapped sediment, but that the chemical band isotopic variation reflects carbonate deposition in an environment where different water masses mixed. Calculated Nd flux ratios yield a hydrothermal input into the 2.52 Ga oceans one order of magnitude larger than continental input. Such a change in flux ratio most likely required substantially reduced continental inputs, which could, in turn, reflect a plate tectonic causation (e.g., reduced topography or expansion of epicontinental seas). Copyright (C) 2001 Elsevier Science Ltd.
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The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.
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Generally employment has been studied in terms of changes in the types of goods and services that the economy is purchasing. Far less attention has been given to the occupational aggregates that go into producing these goods and services. The few studies that did investigate this area found that the mix of tabour inputs appear to have been changing over time in a systematic pattern. The increasing prevalence of white-collar, information workers gave rise to the assertion that many societies had entered a post-industrial information age. Deals first of aff with some issues of measurement in the context of the Australian labour force, then looks at trends in various occupational groups using a non-standard four-sector classification of the labour force. Finally suggests an application in relation to the link between education and training and its ability to reduce structural unemployment.
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A novel bloom of the surf diatom Anaulus australis Drebes et Schultz was observed in subtropical waters off Surfers' Paradise, Queensland, Australia (27 degrees 55'S; 153 degrees 23'E) in early May 2000. This is the lowest latitude in which an Anaulus australis surf diatom bloom has been reported. Nitrogen stable isotope analysis of surf diatoms may indicate anthropogenic nutrient inputs in this environment.
Resumo:
Use of chemical inputs such as pesticides has increased agricultural production and productivity. However, negative externalities from such use have increased too. These externalities include damage to agricultural land, fisheries, fauna and flora. Another major externality is the unintentional destruction of beneficial predators of pests thereby increasing the virulence of many species of agricultural pests. Furthermore, increased mortality and morbidity of humans due to exposure to pesticides are recorded especially in developing countries. The costs from these externalities are large and affect farmers' returns. However, despite these high costs, farmers continue to use pesticides and in most countries in increasing quantities. In this paper, we examine this paradox and show why farmers continue to use pesticides despite the increasing costs. We also emphasize 'lock-in' aspects of pesticide use. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
Increased nitrogen loading has been implicated in eutrophication occurrences worldwide. Much of this loading is attributable to the growing human population along the world's coastlines. A significant component of this nitrogen input is from sewage effluent, and delineation of the distribution and biological impact of sewage-derived nitrogen is becoming increasingly important. Here, we show a technique that identifies the source, extent and fate of biologically available sewage nitrogen in coastal marine ecosystem. This method is based on the uptake of sewage nitrogen by marine plants and subsequent analysis of the sewage signature (elevated delta N-15) in plant tissues. Spatial analysis is used to create maps of delta N-15 and establish coefficient of variation estimates of the mapped values. We show elevated delta N-15 levels in marine plants near sewage outfalls in Moreton Bay, Australia, a semi-enclosed bay receiving multiple sewage inputs. These maps of sewage nitrogen distribution are being used to direct nutrient reduction strategies in the region and will assist in monitoring the effectiveness of environmental protection measures. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
There is a pressing need to address productivity analysis in the hospitality industry if hotels are to exist as sustainable business entities in rapidly maturing markets. Unfortunately, productivity ratios commonly used by managers are narrowly defined. This study illustrates data envelopment analysis of cross-sectional data that benchmark hotels on observed best performances. Data envelopment analysis enables management to integrate unlike multiple inputs and outputs to make simultaneous comparisons. Findings from the cross-sectional data suggest that some of the hotels have the potential to reduce number of beds and number of part-time staff while increasing revenue.
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We show how polarization measurements on the output fields generated by parametric down conversion will reveal a violation of multiparticle Bell inequalities, in the regime of both low- and high-output intensity. In this case, each spatially separated system, upon which a measurement is performed, is comprised of more than one particle. In view of the formal analogy with spin systems, the proposal provides an opportunity to test the predictions of quantum mechanics for spatially separated higher spin states. Here the quantum behavior possible even where measurements are performed on systems of large quantum (particle) number may be demonstrated. Our proposal applies to both vacuum-state signal and idler inputs, and also to the quantum-injected parametric amplifier as studied by De Martini The effect of detector inefficiencies is included, and weaker Bell-Clauser-Horne inequalities are derived to enable realistic tests of local hidden variables with auxiliary assumptions for the multiparticle situation.
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Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.
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The measurement of natural N-15 abundance is a well-established technique for the identification and quantification of biological N-2 fixation in plants. Associative N-2 fixing bacteria have been isolated from sugarcane and reported to contribute potentially significant amounts of N to plant growth and development. It has not been established whether Australian commercial sugarcane receives significant input from biological N-2 fixation, even though high populations of N-2 fixing bacteria have been isolated from Australian commercial sugarcane fields and plants. In this study, delta(15)N measurements were used as a primary measure to identify whether Australian commercial sugarcane was obtaining significant inputs of N via biological N-2 fixation. Quantification of N input, via biological N-2 fixation, was not possible since suitable non-N-2 fixing reference plants were not present in commercial cane fields. The survey of Australian commercially grown sugarcane crops showed the majority had positive leaf delta(15)N values (73% >3.00parts per thousand, 63% of which were
Resumo:
In recent years, studies on environmental samples with unusual dibenzo-p-dioxin (PCDD) congener profiles were reported from a range of countries. These profiles, characterized by a dominance of octachlorinated dibenzodioxin (OCDD) and relatively low in dibenzofuran (PCDF) concentrations, could not be attributed to known sources or formation processes. In the present study, the processes that result in these unusual profiles were assessed using the concentrations and isomer signatures of PCDDs from dated estuarine sediment cores in Queensland, Australia. Increases in relative concentrations of lower chlorinated PODS and a relative decrease of OCDD were correlated with time of sediment deposition. Preferred lateral, anaerobic dechlorination of OCDD represents a likely pathway for these changes. In Queensland sediments, these transformations result in a distinct dominance of isomers fully chlorinated in the 1,4,6,9-positions (1,4-patterns), and similar 1,4-patterns were observed in sediments from elsewhere. Consequently, these environmental samples may not reflect the signatures of the original source, and a reevaluation of source inputs was undertaken. Natural formation of PCDDs, which has previously been suggested, is discussed; however, based on the present results and literature comparisons, we propose an alternative scenario. This scenario hypothesizes that an anthropogenic PCDD precursor input (e.g. pentachlorophenol) results in the contamination. These results and hypothesis imply further investigations are warrented into possible anthropogenic sources in areas where natural PCDD formation has been suggested.
Resumo:
The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.
Resumo:
The central nucleus of the amygdala (CeA) is activated robustly by an immune challenge such as the systemic administration of the proinflammatory cytokine interleukin-1beta (IL-1beta). Because IL-1beta is not believed to cross the blood-brain barrier in any significant amount, it is likely that IL-1beta elicits CeA cell recruitment by means of activation of afferents to the CeA. However, although many studies have investigated the origins of afferent inputs to the CeA, we do not know which of these also respond to IL-1beta. Therefore, to identify candidate neurons responsible for the recruitment of CeA cells by an immune challenge, we iontophoretically deposited a retrograde tracer, cholera toxin b-subunit (CTb), into the CeA of rats 7 days before systemic delivery of IL-1beta (1 mug/kg, i.a.). By using combined immunohistochemistry, we then quantified the number of Fos-positive CTb cells in six major regions known to innervate the CeA. These included the medial prefrontal cortex, paraventricular thalamus (PVT), ventral tegmental area, parabrachial nucleus (PB), nucleus tractus solitarius, and ventrolateral medulla. Our results show that after deposit of CTb into the CeA, the majority of double-labeled cells were located in the PB and the PVT, suggesting that CeA cell activation by systemic IL-1beta is likely to arise predominantly from cell bodies located in these regions. These findings may have significant implications in determining the central pathways involved in generating acute central responses to a systemic immune challenge. J. Comp. Neurol. 452:288-296, 2002. (C) 2002 Wiley-Liss, Inc.
Resumo:
Recent studies have revealed striking differences in pyramidal cell structure among cortical regions involved in the processing of different functional modalities. For example, cells involved in visual processing show systematic variation, increasing in morphological complexity with rostral progression from V1 through extrastriate areas. Differences have also been identified between pyramidal cells in somatosensory, motor and prefrontal cortex, but the extent to which the pyramidal cell phenotype may vary between these functionally related cortical regions remains unknown. In the present study we investigated the structure of layer III pyramidal cells in somatosensory and motor areas 3b, 4, 5, 6 and 7b of the macaque monkey. Cells were intracellularly injected in fixed, flat-mounted cortical slices and analysed for morphometric parameters. The size of the basal dendritic arbours, the number of their branches and their spine density were found to vary systematically between areas. Namely, we found a trend for increasing complexity in dendritic arbour structure through areas 3b, 5 and 7b. A similar trend occurred through areas 4 and 6. The differences in arbour structure may determine the number of inputs received by neurons and may thus be an important factor in determining function at the cellular and systems level.