946 resultados para Morphological characteristic


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Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

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Recent advances in the area of ‘Transformational Government’ position the citizen at the centre of focus. This paradigm shift from a department-centric to a citizen-centric focus requires governments to re-think their approach to service delivery, thereby decreasing costs and increasing citizen satisfaction. The introduction of franchises as a virtual business layer between the departments and their citizens is intended to provide a solution. Franchises are structured to address the needs of citizens independent of internal departmental structures. For delivering services online, governments pursue the development of a One-Stop Portal, which structures information and services through those franchises. Thus, each franchise can be mapped to a specific service bundle, which groups together services that are deemed to be of relevance to a specific citizen need. This study focuses on the development and evaluation of these service bundles. In particular, two research questions guide the line of investigation of this study: Research Question 1): What methods can be used by governments to identify service bundles as part of governmental One-Stop Portals? Research Question 2): How can the quality of service bundles in governmental One-Stop Portals be evaluated? The first research question asks about the identification of suitable service bundle identification methods. A literature review was conducted, to, initially, conceptualise the service bundling task, in general. As a consequence, a 4-layer model of service bundling and a morphological box were created, detailing characteristics that are of relevance when identifying service bundles. Furthermore, a literature review of Decision-Support Systems was conducted to identify approaches of relevance in different bundling scenarios. These initial findings were complemented by targeted studies of multiple leading governments in the e-government domain, as well as with a local expert in the field. Here, the aim was to identify the current status of online service delivery and service bundling in practice. These findings led to the conceptualising of two service bundle identification methods, applicable in the context of Queensland Government: On the one hand, a provider-driven approach, based on service description languages, attributes, and relationships between services was conceptualised. As well, a citizen-driven approach, based on analysing the outcomes from content identification and grouping workshops with citizens, was also conceptualised. Both methods were then applied and evaluated in practice. The conceptualisation of the provider-driven method for service bundling required the initial specification of relevant attributes that could be used to identify similarities between services called relationships; these relationships then formed the basis for the identification of service bundles. This study conceptualised and defined seven relationships, namely ‘Co-location’, ‘Resource’, ‘Co-occurrence’, ‘Event’, ‘Consumer’, ‘Provider’, and ‘Type’. The relationships, and the bundling method itself, were applied and refined as part of six Action Research cycles in collaboration with the Queensland Government. The findings show that attributes and relationships can be used effectively as a means for bundle identification, if distinct decision rules are in place to prescribe how services are to be identified. For the conceptualisation of the citizen-driven method, insights from the case studies led to the decision to involve citizens, through card sorting activities. Based on an initial list of services, relevant for a certain franchise, participating citizens grouped services according to their liking. The card sorting activity, as well as the required analysis and aggregation of the individual card sorting results, was analysed in depth as part of this study. A framework was developed that can be used as a decision-support tool to assist with the decision of what card sorting analysis method should be utilised in a given scenario. The characteristic features associated with card sorting in a government context led to the decision to utilise statistical analysis approaches, such as cluster analysis and factor analysis, to aggregate card sorting results. The second research question asks how the quality of service bundles can be assessed. An extensive literature review was conducted focussing on bundle, portal, and e-service quality. It was found that different studies use different constructs, terminology, and units of analysis, which makes comparing these models a difficult task. As a direct result, a framework was conceptualised, that can be used to position past and future studies in this research domain. Complementing the literature review, interviews conducted as part of the case studies with leaders in e-government, indicated that, typically, satisfaction is evaluated for the overall portal once the portal is online, but quality tests are not conducted during the development phase. Consequently, a research model which appropriately defines perceived service bundle quality would need to be developed from scratch. Based on existing theory, such as Theory of Reasoned Action, Expectation Confirmation Theory, and Theory of Affordances, perceived service bundle quality was defined as an inferential belief. Perceived service bundle quality was positioned within the nomological net of services. Based on the literature analysis on quality, and on the subsequent work of a focus group, the hypothesised antecedents (descriptive beliefs) of the construct and the associated question items were defined and the research model conceptualised. The model was then tested, refined, and finally validated during six Action Research cycles. Results show no significant difference in higher quality or higher satisfaction among users for either the provider-driven method or for the citizen-driven method. The decision on which method to choose, it was found, should be based on contextual factors, such as objectives, resources, and the need for visibility. The constructs of the bundle quality model were examined. While the quality of bundles identified through the citizen-centric approach could be explained through the constructs ‘Navigation’, ‘Ease of Understanding’, and ‘Organisation’, bundles identified through the provider-driven approach could be explained solely through the constructs ‘Navigation’ and ‘Ease of Understanding’. An active labelling style for bundles, as part of the provider-driven Information Architecture, had a larger impact on ‘Quality’ than the topical labelling style used in the citizen-centric Information Architecture. However, ‘Organisation’, reflecting the internal, logical structure of the Information Architecture, was a significant factor impacting on ‘Quality’ only in the citizen-driven Information Architecture. Hence, it was concluded that active labelling can compensate for a lack of logical structure. Further studies are needed to further test this conjecture. Such studies may involve building alternative models and conducting additional empirical research (e.g. use of an active labelling style for the citizen-driven Information Architecture). This thesis contributes to the body of knowledge in several ways. Firstly, it presents an empirically validated model of the factors explaining and predicting a citizen’s perception of service bundle quality. Secondly, it provides two alternative methods that can be used by governments to identify service bundles in structuring the content of a One-Stop Portal. Thirdly, this thesis provides a detailed narrative to suggest how the recent paradigm shift in the public domain, towards a citizen-centric focus, can be pursued by governments; the research methodology followed by this study can serve as an exemplar for governments seeking to achieve a citizen-centric approach to service delivery.

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Currently there are ~3000 known species of Sarcophagidae (Diptera), which are classified into 173 genera in three subfamilies. Almost 25% of sarcophagids belong to the genus Sarcophaga (sensu lato) however little is known about the validity of, and relationships between the ~150 (or more) subgenera of Sarcophaga s.l. In this preliminary study, we evaluated the usefulness of three sources of data for resolving relationships between 35 species from 14 Sarcophaga s.l. subgenera: the mitochondrial COI barcode region, ~800. bp of the nuclear gene CAD, and 110 morphological characters. Bayesian, maximum likelihood (ML) and maximum parsimony (MP) analyses were performed on the combined dataset. Much of the tree was only supported by the Bayesian and ML analyses, with the MP tree poorly resolved. The genus Sarcophaga s.l. was resolved as monophyletic in both the Bayesian and ML analyses and strong support was obtained at the species-level. Notably, the only subgenus consistently resolved as monophyletic was Liopygia. The monophyly of and relationships between the remaining Sarcophaga s.l. subgenera sampled remain questionable. We suggest that future phylogenetic studies on the genus Sarcophaga s.l. use combined datasets for analyses. We also advocate the use of additional data and a range of inference strategies to assist with resolving relationships within Sarcophaga s.l.

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In situ atomic force microscopy (AFM) allows images from the upper face and sides of TCNQ crystals to be monitored during the course of the electrochemical solid–solid state conversion of 50 × 50 μm2 three-dimensional drop cast crystals of TCNQ to CuTCNQ or M[TCNQ]2(H2O)2 (M = Co, Ni). Ex situ images obtained by scanning electron microscopy (SEM) also allow the bottom face of the TCNQ crystals, in contact with the indium tin oxide or gold electrode surface and aqueous metal electrolyte solution, to be examined. Results show that by carefully controlling the reaction conditions, nearly mono-dispersed, rod-like phase I CuTCNQ or M[TCNQ]2(H2O)2 can be achieved on all faces. However, CuTCNQ has two different phases, and the transformation of rod-like phase 1 to rhombic-like phase 2 achieved under conditions of cyclic voltammetry was monitored in situ by AFM. The similarity of in situ AFM results with ex situ SEM studies accomplished previously implies that the morphology of the samples remains unchanged when the solvent environment is removed. In the process of crystal transformation, the triple phase solid∣electrode∣electrolyte junction is confirmed to be the initial nucleation site. Raman spectra and AFM images suggest that 100% interconversion is not always achieved, even after extended electrolysis of large 50 × 50 μm2 TCNQ crystals.

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Drosophila melanogaster, along with all insects and the vertebrates, lacks an RdRp gene. We created transgenic strains of Drosophila melanogaster in which the rrf-1 or ego-1 RdRp genes from C. elegans were placed under the control of the yeast GAL4 upstream activation sequence. Activation of the gene was performed by crossing these lines to flies carrying the GAL4 transgene under the control of various Drosophila enhancers. RT-PCR confirmed the successful expression of each RdRp gene. The resulting phenotypes indicated that introduction of the RdRp genes had no effect on D. melanogaster morphological development. © 2010 Springer Science+Business Media B.V.

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Ozone-induced dissociation (OzID) is an alternative ion activation method that relies on the gas phase ion-molecule reaction between a mass-selected target ion and ozone in an ion trap mass spectrometer. Herein, we evaluated the performance of OzID for both the structural elucidation and selective detection of conjugated carbon-carbon double bond motifs within lipids. The relative reactivity trends for \[M + X](+) ions (where X = Li, Na, K) formed via electrospray ionization (ESI) of conjugated versus nonconjugated fatty acid methyl esters (FAMEs) were examined using two different OzID-enabled linear ion-trap mass spectrometers. Compared with nonconjugated analogues, FAMEs derived from conjugated linoleic acids were found to react up to 200 times faster and to yield characteristic radical cations. The significantly enhanced reactivity of conjugated isomers means that OzID product ions can be observed without invoking a reaction delay in the experimental sequence (i.e., trapping of ions in the presence of ozone is not required). This possibility has been exploited to undertake neutral-loss scans on a triple quadrupole mass spectrometer targeting characteristic OzID transitions. Such analyses reveal the presence of conjugated double bonds in lipids extracted from selected foodstuffs. Finally, by benchmarking of the absolute ozone concentration inside the ion trap, second order rate constants for the gas phase reactions between unsaturated organic ions and ozone were obtained. These results demonstrate a significant influence of the adducting metal on reaction rate constants in the fashion Li > Na > K.

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Frizzled (FZD) receptors have a conserved N-terminal extracellular cysteine-rich domain that interacts with Wnts and co-expression of the receptor ectodomain can antagonize FZD-mediated signalling. Using the ectodomain as an antagonist we have modulated endogenous FZD7 signalling in the moderately differentiated colon adenocarcinoma cell line, SK-CO-1. Unlike the parental cell line, which grows as tightly associated adherent cell clusters, the FZD7 ectodomain expressing cells display a spread out morphology and grow as a monolayer in tissue culture. This transition in morphology was associated with decreased levels of plasma membrane-associated E-cadherin and β-catenin, localized increased levels of vimentin and redistribution of α6 integrin to cellular processes in the FZD7 ectodomain expressing cells. The morphological and phenotype changes induced by FZD7 ectodomain expression in SK-CO-1 cells is thus consistent with the cells undergoing an epithelial-to-mesenchymal-like transition. Furthermore, initiation of tumor formation in a xenograft tumor growth assay was attenuated in the FZD7 ectodomain expressing cells. Our results indicate a pivotal role for endogenous FZD7 in morphology transitions that are associated with colon tumor initiation and progression.

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Information on the variation available for different plant attributes has enabled germplasm collections to be effectively utilised in plant breeding. A world sourced collection of white clover germplasm has been developed at the White Clover Resource Centre at Glen Innes, New South Wales. This collection of 439 accessions was characterised under field conditions as a preliminary study of the genotypic variation for morphological attributes; stolon density, stolon branching, number of nodes. number of rooted nodes, stolon thickness, internode length, leaf length, plant height and plant spread, together with seasonal herbage yield. Characterisation was conducted on different batches of germplasm (subsets of accessions taken from the complete collection) over a period of five years. Inclusion of two check cultivars, Haifa and Huia, in each batch enabled adjustment of the characterisation data for year effects and attribute-by-year interaction effects. The component of variance for seasonal herbage yield among batches was large relative to that for accessions. Accession-by-experiment and accession-by-season interactions for herbage yield were not detected. Accession mean repeatability for herbage yield across seasons was intermediate (0.453). The components of genotypic variance among accessions for all attributes, except plant height, were larger than their respective standard errors. The estimates of accession mean repeatability for the attributes ranged from low (0.277 for plant height) to intermediate (0.544 for internode length). Multivariate techniques of clustering and ordination were used to investigate the diversity present among the accessions in the collection. Both cluster analysis and principal component analysis suggested that seven groups of accessions existed. It was also proposed from the pattern analysis results that accessions from a group characterised by large leaves, tall plants and thick stolons could be crossed with accessions from a group that had above average stolon density and stolon branching. This material could produce breeding populations to be used in recurrent selection for the development of white clover cultivars for dryland summer moisture stress environments in Australia. The germplasm collection was also found to be deficient in genotypes with high stolon density, high number of branches high number of rooted nodes and large leaves. This warrants addition of new germplasm accessions possessing these characteristics to the present germplasm collection.

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Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

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Slippage in the contact roller-races has always played a central role in the field of diagnostics of rolling element bearings. Due to this phenomenon, vibrations triggered by a localized damage are not strictly periodic and therefore not detectable by means of common spectral functions as power spectral density or discrete Fourier transform. Due to the strong second order cyclostationary component, characterizing these signals, techniques such as cyclic coherence, its integrated form and square envelope spectrum have proven to be effective in a wide range of applications. An expert user can easily identify a damage and its location within the bearing components by looking for particular patterns of peaks in the output of the selected cyclostationary tool. These peaks will be found in the neighborhood of specific frequencies, that can be calculated in advance as functions of the geometrical features of the bearing itself. Unfortunately the non-periodicity of the vibration signal is not the only consequence of the slippage: often it also involves a displacement of the damage characteristic peaks from the theoretically expected frequencies. This issue becomes particularly important in the attempt to develop highly automated algorithms for bearing damage recognition, and, in order to correctly set thresholds and tolerances, a quantitative description of the magnitude of the above mentioned deviations is needed. This paper is aimed at identifying the dependency of the deviations on the different operating conditions. This has been possible thanks to an extended experimental activity performed on a full scale bearing test rig, able to reproduce realistically the operating and environmental conditions typical of an industrial high power electric motor and gearbox. The importance of load will be investigated in detail for different bearing damages. Finally some guidelines on how to cope with such deviations will be given, accordingly to the expertise obtained in the experimental activity.

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Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

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This thesis developed a high preforming alternative numerical technique to investigate microscale morphological changes of plant food materials during drying. The technique is based on a novel meshfree method, and is more capable of modeling large deformations of multiphase problem domains, when compared with conventional grid-based numerical modeling techniques. The developed cellular model can effectively replicate dried tissue morphological changes such as shrinkage and cell wall wrinkling, as influenced by moisture reduction and turgor loss.

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Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.