956 resultados para Maria, archduchess of Austria, 1551-1608.
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This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.
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This paper studies the effect of rain on travel demand measured on the Tokyo Metropolitan Expressway (MEX). Rainfall data monitored by the Japan Meteorological Agency's meso-scale network of weather stations are used. This study found that travel demand decreases during rainy days and, in particular, larger reductions occur over the weekend. The effect of rainfall on the number of accidents recorded on 10 routes on the MEX is also analysed. Statistical testing shows that the average frequency of accidents, during periods of rainfall, is significantly different from the average frequency at other times.
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Light Transport Systems (LTS) (e.g lightpipes, fibre optics) can illuminate core areas within buildings with great potential for energy savings. However, they do not provide a clear connection to the outside like windows do, and their effects on people’s physiological and psychological health are not well understood. Furthermore, how people perceive LTS affects users’ acceptance of the device and its performance. The purpose of this research is to understand how occupants perceive and experience spaces illuminated by LTS. Two case studies of commercial buildings with LTS, located in Brisbane, Australia are assessed by qualitative (focus group interviews) and quantitative (measurement of daylight illuminances and luminance) methods. The data from interviews with occupants provide useful insight into the aspects of LTS design that are most relevant to positive perception of the luminous environment. Luminance measurements of the occupied spaces support the perception of the LTS reported by occupants: designs that create high contrast luminous environments are more likely to be perceived negatively.
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To undertake exploratory benchmarking of a set of clinical indicators of quality care in residential care in Australia, data were collected from 107 residents within four medium-sized facilities (40–80 beds) in Brisbane, Australia. The proportion of residents in each sample facility with a particular clinical problem was compared with US Minimum Data Set quality indicator thresholds. Results demonstrated variability within and between clinical indicators, suggesting breadth of assessment using various clinical indicators of quality is an important factor when monitoring quality of care. More comprehensive and objective measures of quality of care would be of great assistance in determining and monitoring the effectiveness of residential aged care provision in Australia, particularly as demands for accountability by consumers and their families increase. What is known about the topic? The key to quality improvement is effective quality assessment, and one means of evaluating quality of care is through clinical outcomes. The Minimum Data Set quality indicators have been credited with improving quality in United States nursing homes. What does this paper add? The Clinical Care Indicators Tool was used to collect data on clinical outcomes, enabling comparison of data from a small Australian sample with American quality benchmarks to illustrate the utility of providing guidelines for interpretation. What are the implications for practitioners? Collecting and comparing clinical outcome data would enable practitioners to better understand the quality of care being provided and whether practices required review. The Clinical Care Indicator Tool could provide a comprehensive and systematic means of doing this, thus filling a gap in quality monitoring within Australian residential aged care.
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This overview focuses on the application of chemometrics techniques for the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals because these two important and very diverse groups of pollutants are ubiquitous in soils. The salient features of various studies carried out in the micro- and recreational environments of humans, are highlighted in the context of the various multivariate statistical techniques available across discipline boundaries that have been effectively used in soil studies. Particular attention is paid to techniques employed in the geosciences that may be effectively utilized for environmental soil studies; classical multivariate approaches that may be used in isolation or as complementary methods to these are also discussed. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contaminant source contributions to a particular site, have seen little use in soil studies, but may be effectively employed in such investigations. Suitable programs are also available for suggesting mitigating measures in cases of soil contamination, and these are also considered. Specific techniques reviewed include pattern recognition techniques such as Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); geostatistical tools include variograms, Geographical Information Systems (GIS), contour mapping and kriging; source identification and contribution estimation methods reviewed include Positive Matrix Factorisation (PMF), and Principal Component Analysis on Absolute Principal Component Scores (PCA/APCS). Mitigating measures to limit or eliminate pollutant sources may be suggested through the use of ranking analysis and multi criteria decision making methods (MCDM). These methods are mainly represented in this review by studies employing the Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).
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We aim to fabricate computer-controlled hydrogel structures containing viable encapsulated cells to overcome the low seeding densities which are inherent to most pre-fabricated scaffold systems.
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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.
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This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.
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Background: In response to the need for more comprehensive quality assessment within Australian residential aged care facilities, the Clinical Care Indicator (CCI) Tool was developed to collect outcome data as a means of making inferences about quality. A national trial of its effectiveness and a Brisbane-based trial of its use within the quality improvement context determined the CCI Tool represented a potentially valuable addition to the Australian aged care system. This document describes the next phase in the CCI Tool.s development; the aims of which were to establish validity and reliability of the CCI Tool, and to develop quality indicator thresholds (benchmarks) for use in Australia. The CCI Tool is now known as the ResCareQA (Residential Care Quality Assessment). Methods: The study aims were achieved through a combination of quantitative data analysis, and expert panel consultations using modified Delphi process. The expert panel consisted of experienced aged care clinicians, managers, and academics; they were initially consulted to determine face and content validity of the ResCareQA, and later to develop thresholds of quality. To analyse its psychometric properties, ResCareQA forms were completed for all residents (N=498) of nine aged care facilities throughout Queensland. Kappa statistics were used to assess inter-rater and test-retest reliability, and Cronbach.s alpha coefficient calculated to determine internal consistency. For concurrent validity, equivalent items on the ResCareQA and the Resident Classification Scales (RCS) were compared using Spearman.s rank order correlations, while discriminative validity was assessed using known-groups technique, comparing ResCareQA results between groups with differing care needs, as well as between male and female residents. Rank-ordered facility results for each clinical care indicator (CCI) were circulated to the panel; upper and lower thresholds for each CCI were nominated by panel members and refined through a Delphi process. These thresholds indicate excellent care at one extreme and questionable care at the other. Results: Minor modifications were made to the assessment, and it was renamed the ResCareQA. Agreement on its content was reached after two Delphi rounds; the final version contains 24 questions across four domains, enabling generation of 36 CCIs. Both test-retest and inter-rater reliability were sound with median kappa values of 0.74 (test-retest) and 0.91 (inter-rater); internal consistency was not as strong, with a Chronbach.s alpha of 0.46. Because the ResCareQA does not provide a single combined score, comparisons for concurrent validity were made with the RCS on an item by item basis, with most resultant correlations being quite low. Discriminative validity analyses, however, revealed highly significant differences in total number of CCIs between high care and low care groups (t199=10.77, p=0.000), while the differences between male and female residents were not significant (t414=0.56, p=0.58). Clinical outcomes varied both within and between facilities; agreed upper and lower thresholds were finalised after three Delphi rounds. Conclusions: The ResCareQA provides a comprehensive, easily administered means of monitoring quality in residential aged care facilities that can be reliably used on multiple occasions. The relatively modest internal consistency score was likely due to the multi-factorial nature of quality, and the absence of an aggregate result for the assessment. Measurement of concurrent validity proved difficult in the absence of a gold standard, but the sound discriminative validity results suggest that the ResCareQA has acceptable validity and could be confidently used as an indication of care quality within Australian residential aged care facilities. The thresholds, while preliminary due to small sample size, enable users to make judgements about quality within and between facilities. Thus it is recommended the ResCareQA be adopted for wider use.
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The development of growth factor delivery strategies to circumvent the burst release phenomenon prevalent in most current systems has driven research towards encapsulating molecules in resorbable polymer matrices. For these polymer release techniques to be efficacious in a clinical setting, several key points need to be addressed. This present study has investigated the encapsulation of the growth factor, BMP-2 within PLGA/PLGA-PEG-PLGA microparticles. Morphology, size distribution, encapsulation efficiency and release kinetics were investigated and we have demonstrated a sustained release of bioactive BMP-2. Furthermore, biocompatibility of the PLGA microparticles was established and released BMP-2 was shown to promote the differentiation of MC3T3-E1 cells towards the osteogenic lineage to a greater extent than osteogenic supplements (as early as day 10 in culture), as determined using alkaline phosphatase and alizarin red assays. This study showcases a potential BMP-2 delivery system which may now be translated into more complex delivery systems, such as 3D, mechanically robust scaffolds for bone tissue regeneration applications.
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The explosion in use of online social networks is an important phenomenon that provides a new set of entrepreneurial opportunities. Emerging musicians have been among the first to exploit this new market opportunity – and indeed, many have used it successfully. A recent study Carter (2009) reveals that artists who earned the most returns had an online presence on multiple social online sites and services such as MySpace and Facebook. These web pages are leveraged to build fan bases and develop different types of revenue streams. Yet, little is currently known about discovery or exploitation of such opportunities.
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The ability to reproducibly load bioactive molecules into polymeric microspheres is a challenge. Traditional microsphere fabrication methods typically provide inhomogeneous release profiles and suffer from lack of batch to batch reproducibility, hindering their potential to up-scale and their translation to the clinic. This deficit in homogeneity is in part attributed to broad size distributions and variability in the morphology of particles. It is thus desirable to control morphology and size of non-loaded particles in the first instance, in preparation for obtaining desired release profiles of loaded particles in the later stage. This is achieved by identifying the key parameters involved in particle production and understanding how adapting these parameters affects the final characteristics of particles. In this study, electrospraying was presented as a promising technique for generating reproducible particles made of polycaprolactone, a biodegradable, FDA-approved polymer. Narrow size distributions were obtained by the control of electrospraying flow rate and polymer concentration, with average particle sizes ranging from 10 to 20 um. Particles were shown to be spherical with a homogenous embossed texture, determined by the polymer entanglement regime taking place during electrospraying. No toxic residue was detected by this process based on preliminary cell work using DNA quantification assays, validating this method as suitable for further loading of bioactive components.
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A combustion synthesis of lithium niobate (LN) squares from activated niobium oxide (Nb2 O5.nH2O) and Li2CO3 was studied to understand all the chemical reactions involved, and the nucleation and square-growth mechanisms. It was found that first the lithium ions react with the fuel (urea), then niobium ions of Nb2 O5.nH2O begin a continuous reaction with the fuel to form metal-organic complexes. LN nuclei are formed by the solid-state reaction of Li- and Nb-organic complexes at 430 degrees celcius. Lithium niobate squares are obtained in the crystallization stasge at 700 degrees celcius, which go on the grow into larger squares at 850 degrees celcius because of the agglomeration effect.
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A basic element in advertising strategy is the choice of an appeal. In business-to-business (B2B) marketing communication, a long-standing approach relies on literal and factual, benefit-laden messages. Given the highly complex, costly and involved processes of business purchases, such approaches are certainly understandable. This project challenges the traditional B2B approach and asks if an alternative approach—using symbolic messages that operate at a more intrinsic or emotional level—is effective in the B2B arena. As an alternative to literal (factual) messages, there is an emerging body of literature that asserts stronger, more enduring results can be achieved through symbolic messages (imagery or text) in an advertisement. The present study contributes to this stream of research. From a theoretical standpoint, the study explores differences in literal-symbolic message content in B2B advertisements. There has been much discussion—mainly in the consumer literature—on the ability of symbolic messages to motivate a prospect to process advertising information by necessitating more elaborate processing and comprehension. Business buyers are regarded as less receptive to indirect or implicit appeals because their purchase decisions are based on direct evidence of product superiority. It is argued here, that these same buyers may be equally influenced by advertising that stimulates internally-directed motivation, feelings and cognitions about the brand. Thus far, studies on the effect of literalism and symbolism are fragmented, and few focus on the B2B market. While there have been many studies about the effects of symbolism no adequate scale exists to measure the continuum of literalism-symbolism. Therefore, a first task for this study was to develop such a scale. Following scale development, content analysis of 748 B2B print advertisements was undertaken to investigate whether differences in literalism-symbolism led to higher advertising performance. Variations of time and industry were also measured. From a practical perspective, the results challenge the prevailing B2B practice of relying on literal messages. While definitive support was not established for the use of symbolic message content, literal messages also failed to predict advertising performance. If the ‘fact, benefit laden’ assumption within B2B advertising cannot be supported, then other approaches used in the business-to-consumer (B2C) sector, such as symbolic messages may be also appropriate in business markets. Further research will need to test the potential effects of such messages, thereby building a revised foundation that can help drive advances in B2B advertising. Finally, the study offers a contribution to the growing body of knowledge on symbolism in advertising. While the specific focus of the study relates to B2B advertising, the Literalism-Symbolism scale developed here provides a reliable measure to evaluate literal and symbolic message content in all print advertisements. The value of this scale to advance our understanding about message strategy may be significant in future consumer and business advertising research.