9 resultados para Data Generation

em University of Queensland eSpace - Australia


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We investigated whether the protection from graft-versus-host disease (GVHD) afforded by donor treatment with granulocyte colony-stimulating factor (G-CSF) could be enhanced by dose escalation. Donor treatment with human G-CSIF prevented GVHD in the B6 --> B6D2F1 murine model in a dose-dependent fashion, and murine G-CSF provided equivalent protection from GVHD at 10-fold lower doses. Donor pretreatment with a single dose of pegylated G-CSF (peg-G-CSF) prevented GVHD to a significantly greater extent than standard G-CSIF (survival, 75% versus 11%, P < .001). Donor T cells from peg-G-CSF-treated donors failed to proliferate to alloantigen and inhibited the responses of control T cells in an interleukin 10 (IL-10)-dependent-fashion in vitro. T cells from peg-GCSF-treated IL-10(-/-) donors induced lethal GVHD; T cells from peg-G-CSF-treated wild-type (wt) donors promoted long-term survival. Whereas T cells from peg-G-CSF wt donors were able to regulate GVHD induced by T cells from control-treated donors, T cells from G-CSF-treated wt donors and peg-G-CSF-treated IL-10(-/-) donors did not prevent mortality. Thus, peg-G-CSF is markedly superior to standard G-CSF for the prevention of GVHD following allogeneic stem cell transplantation (SCT), due to the generation of IL-10-producing regulatory T cells. These data support prospective clinical trials of peg-G-CSF-mobilized allogeneic blood SCT. (C) 2004 by The American Society of Hematology.

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This paper presents new laboratory data on the generation of long waves by the shoaling and breaking of transient-focused short-wave groups. Direct offshore radiation of long waves from the breakpoint is shown experimentally for the first time. High spatial resolution enables identification of the relationship between the spatial gradients of the short-wave envelope and the long-wave surface. This relationship is consistent with radiation stress theory even well inside the surf zone and appears as a result of the strong nonlinear forcing associated with the transient group. In shallow water, the change in depth across the group leads to asymmetry in the forcing which generates significant dynamic setup in front of the group during shoaling. Strong amplification of the incident dynamic setup occurs after short-wave breaking. The data show the radiation of a transient long wave dominated by a pulse of positive elevation, preceded and followed by weaker trailing waves with negative elevation. The instantaneous cross-shore structure of the long wave shows the mechanics of the reflection process and the formation of a transient node in the inner surf zone. The wave run-up and relative amplitude of the radiated and incident long waves suggests significant modification of the incident bound wave in the inner surf zone and, the dominance of long waves generated by the breaking process. It is proposed that these conditions occur when the primary short waves and bound wave are not shallow water waves at the breakpoint. A simple criterion is given to determine these conditions, which generally occur for the important case of storm waves.

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The growth, maintenance and lysis processes of Nitrobacter were characterised. A Nitrobacter culture was enriched in a sequencing batch reactor (SBR). Fluorescent in situ hybridisation showed that Nitrobacter constituted 73% of the bacterial population. Batch tests were carried out to measure the oxygen uptake rate and/or nitrite consumption rate when both nitrite and CO2 were in excess, and in the absence of either of these two substrates. The results obtained, along with the SBR performance data, allowed the determination of the maintenance coefficient and in situ cell lysis rate of Nitrobacter. Nitrobacter spends a significant amount of energy for maintenance, which varies considerably with the specific growth rate. At maximum growth, Nitrobacter consume nitrite at a rate of 0.042 mgN/mgCOD(biomass)center dot h for maintenance purposes, which increases more than threefold to 0.143 mgN/mgCOD(biomass)center dot h in the absence of growth. In the SBR, where Nitrobacter grew at 40% of its maximum growth rate, a maintenance coefficient of 0.113 mgN/mgCOD center dot h was found, resulting in 42% of the total amount of nitrite being consumed for maintenance. The above three maintenance coefficient values obtained at different growth rates appear to support the maintenance model proposed in Pirt (1982). The in situ lysis rate of Nitrobacter was determined to be 0.07/day under aerobic conditions at 22 C and pH 7.3. Further, the maximum specific growth rate of Nitrobacter was estimated to be 0.02/h (0.48/day). The affinity constant of Nitrobacter with respect to nitrite was determined to be 1.50 mgNO(2)(-)-N/L, independent of the presence or absence of CO2. (c) 2006 Wiley Periodicals, Inc.

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The basis of this work was to investigate the relative environmental impacts of various power generators knowing that all plants are located in totally different environments and that different receptors will experience different impacts. Based on IChemE sustainability metrics paradigm, we calculated potential environmental indicators (P-EI) that represent the environmental burden of masses of potential pollutants discharged into different receiving media. However, a P-EI may not be of significance, as it may not be expressed at all in different conditions, so to try and include some receiver significance we developed a methodology to take into account some specific environmental indicators (S-EI) that refer to the environmental attributes of a specific site. In this context, we acquired site specific environmental data related to the airsheds and water catchment areas in different locations for a limited number of environmental indicators such as human health (carcinogenic) effects, atmospheric acidification, photochemical (ozone) smog and eutrophication. The S-EI results from this particular analysis show that atmospheric acidification has highest impact value while health risks due to fly ash emissions are considered not to be as significant. This is due to the fact that many coal power plants in Australia are located in low population density air sheds. The contribution of coal power plants to photochemical (ozone) smog and eutrophication were not significant. In this study, we have considered emission related data trends to reflect technology performance (e.g., P-EI indicators) while a real sustainability metric can be associated only with the specific environmental conditions of the relevant sites (e.g., S-EI indicators).

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A novel method that relies on the decoupling of the energy production and biosynthesis processes was used to characterise the maintenance, cell lysis and growth processes of Nitrosomonas sp. A Nitrosolnonas culture was enriched in a sequencing batch reactor (SBR) with ammonium as the sole energy source. Fluorescent in situ hybridization (FISH) showed that Nitrosomonas bound to the NEU probe constituted 82% of the bacterial population, while no other known ammonium or nitrite oxidizing bacteria were detected. Batch tests were carried out under conditions that both ammonium and CO, were in excess, and in the absence of one of these two substrates. The oxygen uptake rate and nitrite production rate were measured during these batch tests. The results obtained from these batch tests, along with the SBR performance data, allowed the determination of the maintenance coefficient and the in situ cell lysis rate, as well as the maximum specific growth rate of the Nitrosomonas culture. It is shown that, during normal growth, the Nitrosomonas culture spends approximately 65% of the energy generated for maintenance. The maintenance coefficient was determined to be 0.14 - 0.16 mgN mgCOD(biomass)(-1) h(-1), and was shown to be independent of the specific growth rate. The in situ lysis rate and the maximum specific growth rate of the Nitrosomonas culture were determined to be 0.26 and 1.0 day(-1) (0.043 h(-1)), respectively, under aerobic conditions at 30 degrees C and pH7. (c) 2006 Elsevier B.V. All rights reserved.

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A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

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Large amounts of information can be overwhelming and costly to process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities as well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80 % of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by preaggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is "NP-complete.