277 resultados para far field pattern


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Basal cell carcinoma (BCC) is a skin cancer of particular importance to the Australian community. Its rate of occurrence is highest in Queensland, where 1% to 2% of people are newly affected annually. This is an order of magnitude higher than corresponding incidence estimates in European and North American populations. Individuals with a sun-sensitive complexion are particularly susceptible because sun exposure is the single most important causative agent, as shown by the anatomic distribution of BCC which is in general consistent with the levels of sun exposure across body sites. A distinguishing feature of BCC is the occurrence of multiple primary tumours within individuals, synchronously or over time, and their diagnosis and treatment costs contribute substantially to the major public health burden caused by BCC. A primary knowledge gap about BCC pathogenesis however was an understanding of the true frequency of multiple BCC occurrences and their body distribution, and why a proportion of people do develop more than one BCC in their life. This research project sought to address this gap under an overarching research aim to better understand the detailed epidemiology of BCC with the ultimate goal of reducing the burden of this skin cancer through prevention. The particular aim was to document prospectively the rate of BCC occurrence and its associations with constitutional and environmental (solar) factors, all the while paying special attention to persons affected by more than one BCC. The study built on previous findings and recent developments in the field but set out to confirm and extend these and propose more adequate theories about the complex epidemiology of this cancer. Addressing these goals required a new approach to researching basal cell carcinoma, due to the need to account for the phenomenon of multiple incident BCCs per person. This was enabled by a 20 year community-based study of skin cancer in Australians that provided the methodological foundation for this thesis. Study participants were originally randomly selected in 1986 from the electoral register of all adult residents of the subtropical township of Nambour in Queensland, Australia. On various occasions during the study, participants were fully examined by dermatologists who documented cumulative photodamage as well as skin cancers. Participants completed standard questionnaires about skin cancer-related factors, and consented to have any diagnosed skin cancers notified to the investigators by regional pathology laboratories in Queensland. These methods allowed 100% ascertainment of histologically confirmed BCCs in this study population. 1339 participants had complete follow-up to the end of 2007. Statistical analyses in this thesis were carried out using SAS and SUDAAN statistical software packages. Modelling methods, including multivariate logistic regressions, allowed for repeated measures in terms of multiple BCCs per person. This innovative approach gave new findings on two levels, presented in five chapters as scientific papers: 1. Incidence of basal cell carcinoma multiplicity and detailed anatomic distribution: longitudinal study of an Australian population The incidence of people affected multiple times by BCC was 705 per 100,000 person years compared to an incidence rate of people singly affected of 935 per 100,000 person years. Among multiply and singly affected persons alike, site-specific BCC incidence rates were far highest on facial subsites, followed by upper limbs, trunk, and then lower limbs 2. Melanocytic nevi and basal cell carcinoma: is there an association? BCC risk was significantly increased in those with forearm nevi (Odds Ratios (OR) 1.43, 95% Confidence Intervals (CI) 1.09-1.89) compared to people without forearm nevi, especially among those who spent their time mainly outdoors (OR 1.6, 95%CI 1.1-2.3) compared to those who spent their time mainly indoors. Nevi on the back were not associated with BCC. 3. Clinical signs of photodamage are associated with basal cell carcinoma multiplicity and site: a 16-year longitudinal study Over a 16-year follow-up period, 58% of people affected by BCC developed more than one BCC. Among these people 60% developed BCCs across different anatomic sites. Participants with high numbers of solar keratoses, compared to people without solar keratoses, were most likely to experience the highest BCC counts overall (OR 3.3, 95%CI 1.4-13.5). Occurrences of BCC on the trunk (OR 3.3, 95%CI 1.4-7.6) and on the limbs (OR 3.7, 95%CI 2.0-7.0) were strongly associated with high numbers of solar keratoses on these sites. 4. Occurrence and determinants of basal cell carcinoma by histological subtype in an Australian community Among 1202 BCCs, 77% had a single growth pattern and 23% were of mixed histological composition. Among all BCCs the nodular followed by the superficial growth patterns were commonest. Risk of nodular and superficial BCCs on the head was raised if 5 or more solar keratoses were present on the face (OR 1.8, 95%CI 1.2-2.7 and OR 4.5, 95%CI 2.1-9.7 respectively) and similarly on the trunk in the presence of multiple solar keratoses on the trunk (OR 4.2, 95%CI 1.5-11.9 and OR 2.2, 95%CI 1.1-4.4 respectively). 5. Basal cell carcinoma and measures of cumulative sun exposure: an Australian longitudinal community-based study Dermal elastosis was more likely to be seen adjacent to head and neck BCCs than trunk BCCs (p=0.01). Severity of dermal elastosis increased on each site with increasing clinical signs of cutaneous sun damage on that site. BCCs that occurred without perilesional elastosis per se, were always found in an anatomic region with signs of photodamage. This thesis thus has identified the magnitude of the burden of multiple BCCs. It does not support the view that people affected by more than one BCC represent a distinct group of people who are prone to BCCs on certain body sites. The results also demonstrate that BCCs regardless of site, histology or order of occurrence are strongly associated with cumulative sun exposure causing photodamage to the skin, and hence challenge the view that BCCs occurring on body sites with typically low opportunities for sun exposure or of the superficial growth pattern are different in their association with the sun from those on typically sun-exposed sites, or nodular BCCs, respectively. Through dissemination in the scientific and medical literature, and to the community at large, these findings can ultimately assist in the primary and secondary prevention of BCC, perhaps especially in high-risk populations.

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This paper reviews a wide range of literature on environmental management in the field in Queensland, and analyzes this by period and by author. An episodic pattern of activities since European settlement is evident. Periods of exploration (pre-1950) and inventory- compilation (ca. 1950-1970) were followed by two decades of media and non-government organization campaigning (ca. 1970-1990), then an era dominated by government regulatory action (ca. 1990-2010). These eras dominated public perception of what was happening in environmental practice. They were delineated by historic ‘interventions’ (summarily, the end of World War II, the 1971 inflationary crisis, and computerization respectively).

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Introduction The consistency of measuring small field output factors is greatly increased by reporting the measured dosimetric field size of each factor, as opposed to simply stating the nominal field size [1] and therefore requires the measurement of cross-axis profiles in a water tank. However, this makes output factor measurements time consuming. This project establishes at which field size the accuracy of output factors are not affected by the use of potentially inaccurate nominal field sizes, which we believe establishes a practical working definition of a ‘small’ field. The physical components of the radiation beam that contribute to the rapid change in output factor at small field sizes are examined in detail. The physical interaction that dominates the cause of the rapid dose reduction is quantified, and leads to the establishment of a theoretical definition of a ‘small’ field. Methods Current recommendations suggest that radiation collimation systems and isocentre defining lasers should both be calibrated to permit a maximum positioning uncertainty of 1 mm [2]. The proposed practical definition for small field sizes is as follows: if the output factor changes by ±1.0 % given a change in either field size or detector position of up to ±1 mm then the field should be considered small. Monte Carlo modelling was used to simulate output factors of a 6 MV photon beam for square fields with side lengths from 4.0 to 20.0 mm in 1.0 mm increments. The dose was scored to a 0.5 mm wide and 2.0 mm deep cylindrical volume of water within a cubic water phantom, at a depth of 5 cm and SSD of 95 cm. The maximum difference due to a collimator error of ±1 mm was found by comparing the output factors of adjacent field sizes. The output factor simulations were repeated 1 mm off-axis to quantify the effect of detector misalignment. Further simulations separated the total output factor into collimator scatter factor and phantom scatter factor. The collimator scatter factor was further separated into primary source occlusion effects and ‘traditional’ effects (a combination of flattening filter and jaw scatter etc.). The phantom scatter was separated in photon scatter and electronic disequilibrium. Each of these factors was plotted as a function of field size in order to quantify how each affected the change in small field size. Results The use of our practical definition resulted in field sizes of 15 mm or less being characterised as ‘small’. The change in field size had a greater effect than that of detector misalignment. For field sizes of 12 mm or less, electronic disequilibrium was found to cause the largest change in dose to the central axis (d = 5 cm). Source occlusion also caused a large change in output factor for field sizes less than 8 mm. Discussion and conclusions The measurement of cross-axis profiles are only required for output factor measurements for field sizes of 15 mm or less (for a 6 MV beam on Varian iX linear accelerator). This is expected to be dependent on linear accelerator spot size and photon energy. While some electronic disequilibrium was shown to occur at field sizes as large as 30 mm (the ‘traditional’ definition of small field [3]), it has been shown that it does not cause a greater change than photon scatter until a field size of 12 mm, at which point it becomes by far the most dominant effect.

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This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

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Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

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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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Nitrogenated carbon nanotips (NCNTPs) are synthesized by plasma-enhanced hot filament chemical vapor deposition from the hydrogen, methane, and nitrogen gas mixtures with different flow rate ratios of hydrogen to nitrogen. The morphological, structural, compositional, and electron field emission (EFE) properties of the NCNTPs were investigated by field emissionscanning electron microscopy, Raman spectroscopy, x ray photoelectron spectroscopy, and EFE high-vacuum system. It is shown that the NCNTPs deposited at an intermediate flow rate ratio of hydrogen to nitrogen feature the best size/shape and pattern uniformity, the highest nanotip density, the highest nitrogen concentration, as well as the best electron field emission performance. Several factors that come into play along with the nitrogen incorporation, such as the combined effect of the plasma sputtering and etching, the transition of sp 3carbon clusters to sp 2carbon clusters, the increase of the size of the sp 2 clusters, as well as the reduction of the work function, have been examined to interpret these experimental findings. Our results are highly relevant to the development of the next generation electron field emitters, flat panel displays, atomic force microscope probes, and several other advanced applications.

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Aerial applications of granular insecticides are preferable because they can effectively penetrate vegetation, there is less drift, and no loss of product due to evaporation. We aimed to 1) assess the field efficacy ofVectoBac G to control Aedes vigilax (Skuse) in saltmarsh pools, 2) develop a stochastic-modeling procedure to monitor application quality, and 3) assess the distribution of VectoBac G after an aerial application. Because ground-based studies with Ae. vigilax immatures found that VectoBac G provided effective control below the recommended label rate of 7 kg/ha, we trialed a nominated aerial rate of 5 kg/ha as a case study. Our distribution pattern modeling method indicated that the variability in the number of VectoBac G particles captured in catch-trays was greater than expected for 5 kg/ha and that the widely accepted contour mapping approach to visualize the deposition pattern provided spurious results and therefore was not statistically appropriate. Based on the results of distribution pattern modeling, we calculated the catch tray size required to analyze the distribution of aerially applied granular formulations. The minimum catch tray size for products with large granules was 4 m2 for Altosid pellets and 2 m2 for VectoBac G. In contrast, the minimum catch-tray size for Altosid XRG, Aquabac G, and Altosand, with smaller granule sizes, was 1 m2. Little gain in precision would be made by increasing the catch-tray size further, when the increased workload and infrastructure is considered. Our improved methods for monitoring the distribution pattern of aerially applied granular insecticides can be adapted for use by both public health and agricultural contractors.

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This chapter provides an introduction to the use of pedagogical patterns in capturing and sharing educational design experience. In higher education, helping students to learn to engage in productive reflection presents a complex set of challenges. Delicate balances must be found: too little structure and support for students’ reflective work can leave them floundering; too much, and some will remain dependent. Moreover, this is a dynamic teaching problem – scaffolding needs to be adjusted as students develop confidence and capability, which they will do at different rates. The model presented in this chapter embraces the three main elements that teachers can legitimately design, or help set in place, to support their students’ reflective activity: good tasks, the right tools, and appropriate divisions of labour. It delineates a complex, shifting architecture of tasks, tools and people, activities and outcomes associated with reflective learning. It shows how the designable elements of this complex mix can be described in patterns and pattern languages, which then become design resources for teachers’ own action, reflection and professional development.

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Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

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The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.