40 resultados para Bio-sensores


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This paper is concerned with the optimal path planning and initialization interval of one or two UAVs in presence of a constant wind. The method compares previous literature results on synchronization of UAVs along convex curves, path planning and sampling in 2D and extends it to 3D. This method can be applied to observe gas/particle emissions inside a control volume during sampling loops. The flight pattern is composed of two phases: a start-up interval and a sampling interval which is represented by a semi-circular path. The methods were tested in four complex model test cases in 2D and 3D as well as one simulated real world scenario in 2D and one in 3D.

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This thoughtful book is a much needed contribution to feminist ethics that is brimming with detailed and insightful analyses of the positioning of women in contemporary health care and particularly in relation to new reproductive technologies (NRTs). The clearly written and structured chapters provide accessible points to modern ethics, post-modernism, and feminist ethics. Margrit Shildrick takes on these areas with authority and vigour, building an argument for women to enter the relations of reproduction on terms more expressive of feminine desire...

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The utility of a novel technique for determining the ignition delay in a compression ignition engine has been shown. This method utilises statistical modelling in the Bayesian paradigm to accurately resolve the start of combustion from a band-pass in-cylinder pressure signal. Applied to neat diesel and six biofuels, including four fractionations of palm oil of varying carbon chain length and degree of unsaturation, the relationships between ignition delay, cetane number and oxygen content have been explored. It is noted that the expected negative relationship between ignition delay and cetane number held, as did the positive relationship between ignition delay and oxygen content. The degree of unsaturation was also identified as a potential factor influencing the ignition delay.

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This workshop was supported by the Australian Centre for Ecological Analysis and Synthesis (ACEAS, http://www.aceas.org.au/), a facility of the Australian Government-funded Terrestrial Ecosystem Research Network (http://www.tern.org.au/), a research infrastructure facility established under the National Collaborative Research Infrastructure Strategy and Education Infrastructure Fund - Super Science Initiative, through the Department of Industry, Innovation, Science, Research and Tertiary Education. Hosted by: Queensland University of Technology, Brisbane, Queensland. (QUT, http://www.qut.edu.au/) Dates: 8-11 May 2012 Report Editors: Prof Stuart Parsons (Uni. Auckland, NZ) and Dr Michael Towsey (QUT). This report is a compilation of notes and discussion summaries contributed by those attending the Workshop. They have been assembled into a logical order by the editors. Another report (with photographs) can be obtained at: http://www.aceas.org.au/index.php?option=com_content&view=article&id=94&Itemid=96

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This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

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The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.

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Molecular biology is a scientific discipline which has changed fundamentally in character over the past decade to rely on large scale datasets – public and locally generated - and their computational analysis and annotation. Undergraduate education of biologists must increasingly couple this domain context with a data-driven computational scientific method. Yet modern programming and scripting languages and rich computational environments such as R and MATLAB present significant barriers to those with limited exposure to computer science, and may require substantial tutorial assistance over an extended period if progress is to be made. In this paper we report our experience of undergraduate bioinformatics education using the familiar, ubiquitous spreadsheet environment of Microsoft Excel. We describe a configurable extension called QUT.Bio.Excel, a custom ribbon, supporting a rich set of data sources, external tools and interactive processing within the spreadsheet, and a range of problems to demonstrate its utility and success in addressing the needs of students over their studies.

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This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

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A rapid reforming of natural honey exposed to reactive low-temperature Ar + H2 plasmas produced high-quality, ultra-thin vertical graphenes, without any metal catalyst or external heating. This transformation is only possible in the plasma and fails in similar thermal processes. The process is energy-efficient, environmentally benign, and is much cheaper than common synthesis methods based on purified hydrocarbon precursors. The graphenes retain the essential minerals of natural honey, feature reactive open edges and reliable gas- and bio-sensing performance.

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The plasma-assisted RF sputtering deposition of a biocompatible, functionally graded calcium phosphate bioceramic on a Ti6A14 V orthopedic alloy is reported. The chemical composition and presence of hydroxyapatite (HA), CaTiO3, and CaO mineral phases can be effectively controlled by the process parameters. At higher DC biases, the ratio [Ca]/[P] and the amount of CaO increase, whereas the HA content decreases. Optical emission spectroscopy suggests that CaO+ is the dominant species that responds to negative DC bias and controls calcium content. Biocompatibility tests in simulated body fluid confirm a positive biomimetic response evidenced by in-growth of an apatite layer after 24 h of immersion.

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A plasma-assisted concurrent Rf sputtering technique for fabrication of biocompatible, functionally graded CaP-based interlayer on Ti-6Al-4V orthopedic alloy is reported. Each layer in the coating is designed to meet a specific functionality. The adherent to the metal layer features elevated content of Ti and supports excellent ceramic-metal interfacial stability. The middle layer features nanocrystalline structure and mimics natural bone apatites. The technique allows one to reproduce Ca/P ratios intrinsic to major natural calcium phosphates. Surface morphology of the outer, a few to few tens of nanometers thick, layer, has been tailored to fit the requirements for the bio-molecule/protein attachment factors. Various material and surface characterization techniques confirm that the optimal surface morphology of the outer layer is achieved for the process conditions yielding nanocrystalline structure of the middle layer. Preliminary cell culturing tests confirm the link between the tailored nano-scale surface morphology, parameters of the middle nanostructured layer, and overall biocompatibility of the coating.

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Optical emission of reactive plasma species during the synthesis of functionally graded calcium phosphate-based bioactive films has been investigated. The coatings have been deposited on Ti-6Al-4V orthopedic alloy by co-sputtering of hydroxyapatite (HA) and titanium targets in reactive plasmas of Ar + H2O gas mixtures. The species, responsible for the Ca-P-Ti film growth have been non-intrusively monitored in situ by a high-resolution optical emission spectroscopy (OES). It is revealed that the optical emission originating from CaO species dominates throughout the deposition process. The intensities of CaO, PO and CaPO species are strongly affected by variations of the operating pressure, applied RF power, and DC substrate bias. The optical emission intensity (OEI) of reaction species can efficiently be controlled by addition of H2O reactant.

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There is an increased interest on the use of UAVs for environmental research and to track bush fire plumes, volcanic plumes or pollutant sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A memory based and gradient based approach, were developed and compared. A method for generating sparse plumes was also developed. Results indicate the ability of the algorithms to track plumes in 2D and 3D.

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In order to protect our planet and ourselves from the adverse effects of excessive CO2 emissions and to prevent an imminent non-renewable fossil fuel shortage and energy crisis, there is a need to transform our current ‘fossil fuel dependent’ energy systems to new, clean, renewable energy sources. The world has recognized hydrogen as an energy carrier that complies with all the environmental quality and energy security, demands. This research aimed at producing hydrogen through anaerobic fermentation, using food waste as the substrate. Four food waste substrates were used: Rice, fish, vegetable and their mixture. Bio-hydrogen production was performed in lab scale reactors, using 250 mL serum bottles. The food waste was first mixed with the anaerobic sewage sludge and incubated at 37°C for 31 days (acclimatization). The anaerobic sewage sludge was then heat treated at 80°C for 15 min. The experiment was conducted at an initial pH of 5.5 and temperatures of 27, 35 and 55°C. The maximum cumulative hydrogen produced by rice, fish, vegetable and mixed food waste substrates were highest at 37°C (Rice =26.97±0.76 mL, fish = 89.70±1.25 mL, vegetable = 42.00±1.76 mL, mixed = 108.90±1.42 mL). A comparative study of acclimatized (the different food waste substrates were mixed with anaerobic sewage sludge and incubated at 37°C for 31days) and non-acclimatized food waste substrate (food waste that was not incubated with anaerobic sewage sludge) showed that acclimatized food waste substrate enhanced bio-hydrogen production by 90 - 100%.