64 resultados para simultaneous shape and topology optimisation
em University of Queensland eSpace - Australia
Resumo:
The effects of wing shape, wing size, and fluctuating asymmetry in these measures oil the field fitness of T. nr. brassicae and T. pretiosum were investigated. Trichogramma wasps mass-reared on eggs of the factitious host Sitotroga cerealella were released in tomato paddocks and those females ovipositing on Helicoverpo spp. eggs were recaptured. Comparisons of the recaptured group with a sample from the release population were used to assess fitness. Wing data were obtained by positioning landmarks on mounted forewings. Size was then measured as the centroid size computed from landmark distances, while Procrustes analysis followed by principal component analysis was used to assess wing shape. Similar findings were obtained for both Trichogramma species: fitness of wasps was strongly related to wing size and some shape dimensions, but not to the asymmetries of these measures. Wasps which performed well in the field had larger wings and a different wing shape compared to wasps from the mass reared population. Both size and the shape dimensions were linearly associated with fitness although there was also some evidence for non-linear selection on shape. The results suggest that wing shape and wing size are reliable predictors of field fitness for these Trichogramma wasps.
Resumo:
Rhizopus arrhizus, strain DAR 36017, produced L(+)-lactic acid in a simultaneous saccharification and fermentation process using starch waste effluents. Lactic acid at 19.5 - 44.3 g l(-1) with a yield of 0.85 - 0.96 g g(-1) was produced in 40 h using 20 - 60 g starch l(-1). Supplementation of nitrogen source may be unnecessary if potato or corn starch waste effluent was used as a production medium.
Resumo:
Human polyomaviruses JCV and BKV can cause several clinical manifestations in immunocompromised hosts, including progressive multifocal leukoencephalopathy (PML) and haemorrhagic cystitis. Molecular detection by polymerase chain reaction (PCR) is recognised as a sensitive and specific method for detecting human polyomaviruses in clinical samples. In this study, we developed a PCR assay using a single primer pair to amplify a segment of the VP1 gene of JCV and BKV. An enzyme linked amplicon hybridisation assay (ELAHA) using species-specific biotinylated oligonucleotide probes was used to differentiate between JCV and BKV. This assay (VP1-PCR-ELAHA) was evaluated and compared to a PCR assay targeting the human polyomavirus T antigen gene (pol-PCR). DNA sequencing was used to confirm the polyomavirus species identified by the VP1-PCR-ELAHA and to determine the subtype of each JCV isolate. A total of 297 urine specimens were tested and human polyomavirus was detected in 105 specimens (35.4%) by both PCR assays. The differentiation of JCV and BKV by the VP1-PCR-ELAHA showed good agreement with the results of DNA sequencing. Further, DNA sequencing of the JCV positive specimens showed the most prevalent JCV subtype in our cohort was 2a (27%) followed by 1b (20%), 1a (15%), 2c (14%), 4 (14%) and 2b (10%). The results of this study show that the VP1-PCR-ELAHA is a sensitive, specific and rapid method for detecting and differentiating human polyomaviruses JC and BK and is highly suitable for routine use in the clinical laboratory. (C) 2004 Wiley-Liss, Inc.
Resumo:
The biochemical kinetic of simultaneous saccharification and fermentation (SSF) for lactic acid production by fungal species of Rhizopus arrhizus 36017 and Rhizopus oryzae 2062 was studied with respect to growth pH, temperature and substrate. Both R. arrhizus 36017 and R. oryzae 2062 had a capacity to carry out a single stage SSF process for lactic acid production from potato starch wastewater. The kinetic characteristics, termed as starch hydrolysis, accumulation of reducing sugars, lactic acid production and fungal biomass formation, were affected with variations in pH, temperature, and starch source and concentration. A growth condition with starch concentration approximately 20 g/l at pH 6.0 and 30 degrees C was favourable for both starch saccharification and lactic acid fermentation, resulting in lactic acid yield of 0.85-0.92 g/g associated with 1.5-3.5 g/l fungal biomass produced in 36-48 h fermentation. R. arrhizus 36017 had a higher capacity to produce lactic acid, while R. oryzae 2062 produced more fungal biomass under similar conditions. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
We have synthesized ternary InGaAs nanowires on (111)B GaAs surfaces by metal-organic chemical vapor deposition. Au colloidal nanoparticles were employed to catalyze nanowire growth. We observed the strong influence of nanowire density on nanowire height, tapering, and base shape specific to the nanowires with high In composition. This dependency was attributed to the large difference of diffusion length on (111)B surfaces between In and Ga reaction species, with In being the more mobile species. Energy dispersive X-ray spectroscopy analysis together with high-resolution electron microscopy study of individual InGaAs nanowires shows large In/Ga compositional variation along the nanowire supporting the present diffusion model. Photoluminescence spectra exhibit a red shift with decreasing nanowire density due to the higher degree of In incorporation in more sparsely distributed InGaAs nanowires.
Resumo:
The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.
Resumo:
This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.
Resumo:
To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in onedimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.
Resumo:
Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.