46 resultados para GPT


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Field studies show that the internal screens in a gross pollutant trap (GPT) are often clogged with organic matter, due to infrequent cleaning. The hydrodynamic performance of a GPT with fully blocked screens was comprehensively investigated under a typical range of onsite operating conditions. Using an acoustic Doppler velocimeter (ADV), velocity profiles across three critical sections of the GPT were measured and integrated to examine the net fluid flow at each section. The data revealed that when the screens are fully blocked, the flow structure within the GPT radically changes. Consequently, the capture/retention performance of the device rapidly deteriorates. Good agreement was achieved between the experimental and the previous 2D computational fluid dynamics (CFD) velocity profiles for the lower GPT inlet flow conditions.

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A technique was developed to investigate the capture/retention characteristic of a gross pollutant trap (GPT) with fully and partially blocked internal screens. Custom modified spheres of variable density filled with liquid were released into the GPT inlet and monitored at the outlet. The outlet data shows that the capture/retention performances of a GPT with fully blocked screens deteriorate rapidly. During higher flow rates, screen blockages below 68% approach maximum efficiency. At lower flow rates, the high performance trend is reversed and the variation in behaviour of pollutants with different densities becomes more noticeable. Additional experiments with a second upstream inlet configured GPT showed an improved capture/retention performance. It was also noted that the bypass allows the incoming pollutants to escape when the GPT is blocked. This useful feature prevents upstream blockages between cleaning intervals.

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This research shows that gross pollutant traps (GPTs) continue to play an important role in preventing visible street waste—gross pollutants—from contaminating the environment. The demand for these GPTs calls for stringent quality control and this research provides a foundation to rigorously examine the devices. A novel and comprehensive testing approach to examine a dry sump GPT was developed. The GPT is designed with internal screens to capture gross pollutants—organic matter and anthropogenic litter. This device has not been previously investigated. Apart from the review of GPTs and gross pollutant data, the testing approach includes four additional aspects to this research, which are: field work and an historical overview of street waste/stormwater pollution, calibration of equipment, hydrodynamic studies and gross pollutant capture/retention investigations. This work is the first comprehensive investigation of its kind and provides valuable practical information for the current research and any future work pertaining to the operations of GPTs and management of street waste in the urban environment. Gross pollutant traps—including patented and registered designs developed by industry—have specific internal configurations and hydrodynamic separation characteristics which demand individual testing and performance assessments. Stormwater devices are usually evaluated by environmental protection agencies (EPAs), professional bodies and water research centres. In the USA, the American Society of Civil Engineers (ASCE) and the Environmental Water Resource Institute (EWRI) are examples of professional and research organisations actively involved in these evaluation/verification programs. These programs largely rely on field evaluations alone that are limited in scope, mainly for cost and logistical reasons. In Australia, evaluation/verification programs of new devices in the stormwater industry are not well established. The current limitations in the evaluation methodologies of GPTs have been addressed in this research by establishing a new testing approach. This approach uses a combination of physical and theoretical models to examine in detail the hydrodynamic and capture/retention characteristics of the GPT. The physical model consisted of a 50% scale model GPT rig with screen blockages varying from 0 to 100%. This rig was placed in a 20 m flume and various inlet and outflow operating conditions were modelled on observations made during the field monitoring of GPTs. Due to infrequent cleaning, the retaining screens inside the GPTs were often observed to be blocked with organic matter. Blocked screens can radically change the hydrodynamic and gross pollutant capture/retention characteristics of a GPT as shown from this research. This research involved the use of equipment, such as acoustic Doppler velocimeters (ADVs) and dye concentration (Komori) probes, which were deployed for the first time in a dry sump GPT. Hence, it was necessary to rigorously evaluate the capability and performance of these devices, particularly in the case of the custom made Komori probes, about which little was known. The evaluation revealed that the Komori probes have a frequency response of up to 100 Hz —which is dependent upon fluid velocities—and this was adequate to measure the relevant fluctuations of dye introduced into the GPT flow domain. The outcome of this evaluation resulted in establishing methodologies for the hydrodynamic measurements and gross pollutant capture/retention experiments. The hydrodynamic measurements consisted of point-based acoustic Doppler velocimeter (ADV) measurements, flow field particle image velocimetry (PIV) capture, head loss experiments and computational fluid dynamics (CFD) simulation. The gross pollutant capture/retention experiments included the use of anthropogenic litter components, tracer dye and custom modified artificial gross pollutants. Anthropogenic litter was limited to tin cans, bottle caps and plastic bags, while the artificial pollutants consisted of 40 mm spheres with a range of four buoyancies. The hydrodynamic results led to the definition of global and local flow features. The gross pollutant capture/retention results showed that when the internal retaining screens are fully blocked, the capture/retention performance of the GPT rapidly deteriorates. The overall results showed that the GPT will operate efficiently until at least 70% of the screens are blocked, particularly at high flow rates. This important finding indicates that cleaning operations could be more effectively planned when the GPT capture/retention performance deteriorates. At lower flow rates, the capture/retention performance trends were reversed. There is little difference in the poor capture/retention performance between a fully blocked GPT and a partially filled or empty GPT with 100% screen blockages. The results also revealed that the GPT is designed with an efficient high flow bypass system to avoid upstream blockages. The capture/retention performance of the GPT at medium to high inlet flow rates is close to maximum efficiency (100%). With regard to the design appraisal of the GPT, a raised inlet offers a better capture/retention performance, particularly at lower flow rates. Further design appraisals of the GPT are recommended.

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This paper presents a comprehensive review of scientific and grey literature on gross pollutant traps (GPTs). GPTs are designed with internal screens to capture gross pollutants—organic matter and anthropogenic litter. Their application involves professional societies, research organisations, local city councils, government agencies and the stormwater industry—often in partnership. In view of this, the 113 references include unpublished manuscripts from these bodies along with scientific peer-reviewed conference papers and journal articles. The literature reviewed was organised into a matrix of six main devices and nine research areas (testing methodologies) which include: design appraisal study, field monitoring/testing, experimental flow fields, gross pollutant capture/retention characteristics, residence time calculations, hydraulic head loss, screen blockages, flow visualisations and computational fluid dynamics (CFD). When the fifty-four item matrix was analysed, twenty-eight research gaps were found in the tabulated literature. It was also found that the number of research gaps increased if only the scientific literature was considered. It is hoped, that in addition to informing the research community at QUT, this literature review will also be of use to other researchers in this field.

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A novel and comprehensive testing approach to examine the performance of gross pollutant traps (GPTs) was developed. A proprietary GPT with internal screens for capturing gross pollutants—organic matter and anthropogenic litter—was used as a case study. This work is the first investigation of its kind and provides valuable practical information for the design, selection and operation of GPTs and also the management of street waste in an urban environment. It used a combination of physical and theoretical models to examine in detail the hydrodynamic and capture/retention characteristics of the GPT. The results showed that the GPT operated efficiently until at least 68% of the screens were blocked, particularly at high flow rates. At lower flow rates, the high capture/retention performance trend was reversed. It was also found that a raised inlet GPT offered a better capture/retention performance. This finding indicates that cleaning operations could be more effectively planned in conjunction with the deterioration in GPT’s capture/retention performance.

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Typical flow fields in a stormwater gross pollutant trap (GPT) with blocked retaining screens were experimentally captured and visualised. Particle image velocimetry (PIV) software was used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. A technique was developed to apply the Image Based Flow Visualization (IBFV) algorithm to the experimental raw dataset generated by the PIV software. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding gross pollutant capture and retention within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate specific areas and identify the flow features within the GPT.

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Abstract An experimental dataset representing a typical flow field in a stormwater gross pollutant trap (GPT) was visualised. A technique was developed to apply the image-based flow visualisation (IBFV) algorithm to the raw dataset. Particle image velocimetry (PIV) software was previously used to capture the flow field data by tracking neutrally buoyant particles with a high speed camera. The dataset consisted of scattered 2D point velocity vectors and the IBFV visualisation facilitates flow feature characterisation within the GPT. The flow features played a pivotal role in understanding stormwater pollutant capture and retention behaviour within the GPT. It was found that the IBFV animations revealed otherwise unnoticed flow features and experimental artefacts. For example, a circular tracer marker in the IBFV program visually highlighted streamlines to investigate the possible flow paths of pollutants entering the GPT. The investigated flow paths were compared with the behaviour of pollutants monitored during experiments.

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Gross pollutant traps (GPT) are designed to capture and retain visible street waste, such as anthropogenic litter and organic matter. Blocked screens, low/high downstream tidal waters and flows operating above/below the intended design limits can hamper the operations of a stormwater GPT. Under these adverse operational conditions, a recently developed GPT was evaluated. Capture and retention experiments were conducted on a 50% scale model with partially and fully blocked screens, placed inside a hydraulic flume. Flows were established through the model via an upstream channel-inlet configuration. Floatable, partially buoyant, neutrally buoyant and sinkable spheres were released into the GPT and monitored at the outlet. These experiments were repeated with a pipe-inlet configured GPT. The key findings from the experiments were of practical significance to the design, operation and maintenance of GPTs. These involved an optimum range of screen blockages and a potentially improved inlet design for efficient gross pollutant capture/retention operations. For example, the outlet data showed that the capture and retention efficiency deteriorated rapidly when the screens were fully blocked. The low pressure drop across the retaining screens and the reduced inlet flow velocities were either insufficient to mobilise the gross pollutants, or the GPT became congested.

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The tomato I-3 gene introgressed from the Lycopersicon pennellii accession LA716 confers resistance to race 3 of the fusarium wilt pathogen Fusarium oxysporum f. sp. lycopersici. We have improved the high-resolution map of the I-3 region of tomato chromosome 7 with the development and mapping of 31 new PCR-based markers. Recombinants recovered from L. esculentum cv. M82 × IL7-2 F2 and (IL7-2 × IL7-4) × M82 TC1F2 mapping populations, together with recombinants recovered from a previous M82 × IL7-3 F2 mapping population, were used to position these markers. A significantly higher recombination frequency was observed in the (IL7-2 × IL7-4) × M82 TC1F2 mapping population based on a reconstituted L. pennellii chromosome 7 compared to the other two mapping populations based on smaller segments of L. pennellii chromosome 7. A BAC contig consisting of L. esculentum cv. Heinz 1706 BACs covering the I-3 region has also been established. The new high-resolution map places the I-3 gene within a 0.38 cM interval between the molecular markers RGA332 and bP23/gPT with an estimated physical size of 50-60 kb. The I-3 region was found to display almost continuous microsynteny with grape chromosome 12 but interspersed microsynteny with Arabidopsis thaliana chromosomes 1, 2 and 3. An S-receptor-like kinase gene family present in the I-3 region of tomato chromosome 7 was found to be present in the microsyntenous region of grape chromosome 12 but was absent altogether from the A. thaliana genome.

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This study examines Finnish economic growth. The key driver of economic growth was productivity. And the major engine of productivity growth was technology, especially the general purpose technologies (GPTs) electricity and ICT. A new GPT builds on previous knowledge, yet often in an uncertain, punctuated, fashion. Economic history, as well as the Finnish data analyzed in this study, teaches that growth is not a smooth process but is subject to episodes of sharp acceleration and deceleration which are associated with the arrival, diffusion and exhaustion of new general purpose technologies. These are technologies that affect the whole economy by transforming both household life and the ways in which firms conduct business. The findings of previous research, that Finnish economic growth exhibited late industrialisation and significant structural changes were corroborated by this study. Yet, it was not solely a story of manufacturing and structural change was more the effect of than the cause for economic growth. We offered an empirical resolution to the Artto-Pohjola paradox as we showed that a high rate of return on capital was combined with low capital productivity growth. This result is important in understanding Finnish economic growth 1975-90. The main contribution of this thesis was the growth accounting results on the impact of ICT on growth and productivity, as well as the comparison of electricity and ICT. It was shown that ICT s contribution to GDP growth was almost twice as large as electricity s contribution over comparable periods of time. Finland has thus been far more successful as an ICT producer than a producer of electricity. Unfortunately in the use of ICT the results were still more modest than for electricity. During the end of the period considered in this thesis, Finland switched from resource-based to ICT-based growth. However, given the large dependency on the ICT-producing sector, the ongoing outsourcing of ICT production to low wage countries provides a threat to productivity performance in the future. For a developed country only change is constant and history teaches us that it is likely that Finland is obliged to reorganize its economy once again in the digital era.

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Background: Statins may have therapeutic effects on hepatocarcinoma (HCC). This type of disorder is the most common malignant primary tumour in the liver. Our objective was to determine whether pravastatin had a therapeutic effect in vitro and in vivo models. Method: We design in vitro and in vivo model. In vitro we used PLC and determine cell proliferation. In vivo, we used and animal model to determined, PCNA and MAT1A expression and transaminases levels. Results: We found that pravastatin decreases cell proliferation in vitro (cell proliferation in pravastatin group was 82%, in sorafenib group 51% and in combined group 40%) and in vivo (in pravastatin group 80%, in sorafenib group 76.4% and in combined group 72.72%). The MAT1A levels, was significantly higher in Pravastatin group (D 62%, P 94%, S 71%, P + S 91%). The transaminases levels, decreased significantly in Pravastatin group (GOT and GPT levels D 619.5 U/L; 271 U/L) (P 117.5 U/L; 43.5 U/L) (S 147 U/L; 59 U/L) (P + S 142 U/L; 59 U/L). Conclusion: The combination of pravastatin + sorafenib were more effective than Sorafenib alone.

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After stroke, white matter integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption in mirror's regions of the contralateral hemisphere is associated with degree of functional impairment. Fourteen patients suffering right hemispheric focal stroke (S) and eighteen healthy controls (HC) underwent Diffusion Weighted Imaging (DWI) and neuropsychological assessment. The stroke patient group was divided into poor (SP; n = 8) and good (SG; n = 6) cognitive recovery groups according to their cognitive improvement from the acute phase (72 hours after stroke) to the subacute phase (3 months post-stroke). Whole-brain DWI data analysis was performed by computing Diffusion Tensor Imaging (DTI) followed by Tract Based Spatial Statistics (TBSS). Assessment of effects was obtained computing the correlation of the projections on TBSS skeleton of Fractional Anisotropy (FA) and Radial Diffusivity (RD) with cognitive test results. Significant decrease of FA was found only in right brain anatomical areas for the S group when compared to the HC group. Analyzed separately, stroke patients with poor cognitive recovery showed additional significant FA decrease in several left hemisphere regions; whereas SG patients showed significant decrease only in the left genu of corpus callosum when compared to the HC. For the SG group, whole brain analysis revealed significant correlation between the performance in the Semantic Fluency test and the FA in the right hemisphere as well as between the performance in the Grooved Pegboard Test (GPT) and theTrail Making Test-part A and the FA in the left hemisphere. For the SP group, correlation analysis revealed significant correlation between the performance in the GPT and the FA in the right hemisphere. Palabras clave