767 resultados para Biopharmaceutics classification system
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Urban traffic and climate change are two phenomena that have the potential to degrade urban water quality by influencing the build-up and wash-off of pollutants, respectively. However, limited knowledge has made it difficult to establish any link between pollutant buildup and wash-off under such dynamic conditions. In order to safeguard urban water quality, adaptive water quality mitigation measures are required. In this research, pollutant build-up and wash-off have been investigated from a dynamic point of view which incorporated the impacts of changed urban traffic as well as changes in the rainfall characteristics induced by climate change. The study has developed a dynamic object classification system and thereby, conceptualised the study of pollutant build-up and wash-off under future changes in urban traffic and rainfall characteristics. This study has also characterised the buildup and wash-off processes of traffic generated heavy metals, volatile, semi-volatile and non-volatile hydrocarbons under dynamic conditions which enables the development of adaptive mitigation measures for water quality. Additionally, predictive frameworks for the build-up and wash-off of some pollutants have also been developed.
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The International Classification of Diseases (ICD) is used to categorise diseases, injuries and external causes, and is a key epidemiological tool enabling the storage and retrieval of data from health and vital records to produce core international mortality and morbidity statistics. The ICD is updated periodically to ensure the classification remains current and work is now underway to develop the next revision, ICD-11. There have been almost 20 years since the last ICD edition was published and over 60 years since the last substantial structural revision of the external causes chapter. Revision of such a critical tool requires transparency and documentation to ensure that changes made to the classification system are recorded comprehensively for future reference. In this paper, the authors provide a history of external causes classification development and outline the external cause structure. Approaches to manage ICD-10 deficiencies are discussed and the ICD-11 revision approach regarding the development of, rationale for and implications of proposed changes to the chapter are outlined. Through improved capture of external cause concepts in ICD-11, a stronger evidence base will be available to inform injury prevention, treatment, rehabilitation and policy initiatives to ultimately contribute to a reduction in injury morbidity and mortality.
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Background: To derive preference-based measures from various condition-specific descriptive health-related quality of life (HRQOL) measures. A general 2-stage method is evolved: 1) an item from each domain of the HRQOL measure is selected to form a health state classification system (HSCS); 2) a sample of health states is valued and an algorithm derived for estimating the utility of all possible health states. The aim of this analysis was to determine whether confirmatory or exploratory factor analysis (CFA, EFA) should be used to derive a cancer-specific utility measure from the EORTC QLQ-C30. Methods: Data were collected with the QLQ-C30v3 from 356 patients receiving palliative radiotherapy for recurrent or metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter based on a conceptual model (the established domain structure of the QLQ-C30: physical, role, emotional, social and cognitive functioning, plus several symptoms) and clinical considerations (views of both patients and clinicians about issues relevant to HRQOL in cancer). The dimensions determined by each method were then subjected to item response theory, including Rasch analysis. Results: CFA results generally supported the proposed conceptual model, with residual correlations requiring only minor adjustments (namely, introduction of two cross-loadings) to improve model fit (increment χ2(2) = 77.78, p < .001). Although EFA revealed a structure similar to the CFA, some items had loadings that were difficult to interpret. Further assessment of dimensionality with Rasch analysis aligned the EFA dimensions more closely with the CFA dimensions. Three items exhibited floor effects (>75% observation at lowest score), 6 exhibited misfit to the Rasch model (fit residual > 2.5), none exhibited disordered item response thresholds, 4 exhibited DIF by gender or cancer site. Upon inspection of the remaining items, three were considered relatively less clinically important than the remaining nine. Conclusions: CFA appears more appropriate than EFA, given the well-established structure of the QLQ-C30 and its clinical relevance. Further, the confirmatory approach produced more interpretable results than the exploratory approach. Other aspects of the general method remain largely the same. The revised method will be applied to a large number of data sets as part of the international and interdisciplinary project to develop a multi-attribute utility instrument for cancer (MAUCa).
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Australian airports have emerged as important urban activity centres over the past decade as a result of privatisation. A range of reciprocal airport and regional impacts now pose considerable challenges for both airport operation and the surrounding urban and regional environment. The airport can no longer be managed solely as a specialised transport entity in isolation from the metropolis that it serves. In 2007 a multidisciplinary Australian Research Council Linkage Project (LP 0775225) was funded to investigate the changing role of airports in Australia. This thesis is but one component of this collaborative research effort. Here the issues surrounding the policy and practice of airport and regional land use planning are explored, analysed and detailed. This research, for the first time, assembles a distinct progression of the wider social, economic, technological and environmental roles of the airport within the Australian airport literature from 1914 – 2011. It recognises that while the list of airport and regional impacts has grown through time, treatment within practice and the literature has largely remained highly specialised and contained within disciplinary paradigms. The first publication of the thesis (Chapter 2) acknowledges that the changing role of airports demands the establishment of new models of airport planning and development. It argues that practice and research requires a better understanding of the reciprocal impacts of airports and their urban catchments. The second publication (Chapter 3) highlights that there is ad hoc examination and media attention of high profile airport and regional conflict, but little empirical analysis or understanding of the extent to which all privatised Australian airports are intending to develop. The conceptual and methodological significance of this research is the development of a national land use classification system for on-airport development. This paper establishes the extent of on-airport development in Australia, providing insight into the changing land use and economic roles of privatised airports. The third publication (Chapter 4) details new and significant interdependencies for airport and regional development in consideration of the progression of airports as activity centres. Here the model of an ‘airport metropolis’ is offered as an organising device and theoretical contribution for comprehending the complexity and planning of airport and regional development. It delivers a conceptual framework for both research and policy, which acknowledges the reciprocal impacts of economic development, land use, infrastructure and governance ‘interfaces’. In a timely and significant concurrence with this research the Australian Government announced and delivered a National Aviation Policy Review (2008 – 2009). As such the fourth publication (Chapter 5) focuses on the airport and urban planning aspects of the review. This paper also highlights the overall policy intention of facilitating broader airport and regional collaborative processes. This communicative turn in airport policy is significant in light of the communicative theoretical framework of the thesis. The fifth paper of the thesis (Chapter 6) examines three Australian case studies (Brisbane, Adelaide and Canberra) to detail the context of airport and regional land use planning and to apply the airport metropolis model as a framework for research. Through the use of Land Use Forums, over 120 airport and regional stakeholders are brought together to detail their perspectives and interactions with airport and regional land use planning. An inductive thematic analysis of the results identifies three significant themes which contribute to the fragmentation of airport and regional and land use planning: 1) inadequate coordination and disjointed decision-making; 2) current legislative and policy frameworks; and 3) competing stakeholder priorities and interests. Building on this new knowledge, Chapter 7 details the perceptions of airport and local, state and territory government stakeholders to land use relationships, processes and outcomes. A series of semi-structured interviews are undertaken in each of the case studies to inform this research. The potential implications for ongoing communicative practice are discussed in conclusion. The following thesis represents an incremental and cumulative research process which delivers new knowledge for the practical understanding and research interpretation of airport and regional land use planning practice and policy. It has developed and applied a robust conceptual framework which delivers significant direction for all stakeholders to better comprehend the relevance of airports in the urban character and design of our cities.
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Purpose Information on the use of psychotropic medications in adolescents with intellectual disability is scant. Such information can guide interventions to improve psychotropic medication use in this population. We investigated the prevalence of, and factors associated with, psychotropic medication use in adolescents with intellectual disability in Australia who live in the community. Methods Cross-sectional data were obtained from adolescents with intellectual disability living in the community in South East Queensland, Australia, between February 2007 and September 2010. Self-reported information on medication use was extracted from a health screening tool. Demographic and medical data were collected through parent/caregiver surveys. Medications were classified according to the Anatomical Therapeutic Chemical classification system. Psychopathology was assessed using the Developmental Behaviour Checklist Short Form. Logistic regression analysis was used to assess the association of demographic and medical characteristics with psychotropic medication use. Results There were 176 participants (median age = 16 years, range = 11–19 years; 55% male). Psychotropics were used by 20% of participants. Psychostimulants were the commonest psychotropic class, used by 9% of participants. Multipsychotropic prescribing was not common with only seven participants using more than one psychotropic agent. After adjusting for potentially confounding variables, use of psychotropic medications was significantly associated with male gender (adjusted odds ratio = 3.6; 95% confidence interval = 1.3–9.5) and having major behaviour problems (3.1; 1.1–8.9). Conclusions Adolescents with intellectual disability use a wide range of psychotropic medications. Being male and having major behaviour problems are associated with the use of psychotropic medications. Research examining the rationale for psychotropic prescribing in this population is needed. Copyright © 2013 John Wiley & Sons, Ltd.
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The practical need to partition the world of viruses into distinguishable, universally agreed upon entities is the ultimate justification for developing a virus classification system. The Author of this Book is Andrew MQ King, Elliot Lefkowitz, Eric B. Carstens, Michael J. Adams Since 1971, the International Committee on Taxonomy of Viruses (ICTV) operating on behalf of the world community of virologists has taken on the task of developing a single, universal taxonomic scheme for all viruses infecting animals (vertebrate, invertebrates, and protozoa), plants (higher plants and algae), fungi, bacteria, and archaea.
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Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.
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We provide the first molecular phylogeny of the clerid lineage (Coleoptera: Cleridae, Thanerocleridae) within the superfamily Cleroidea to examine the two most recently-proposed hypotheses of higher-level classification. Phylogenetic relationships of checkered beetles were inferred from approximately ~5,000nt of both nuclear and mitochondrial rDNA (28S, 16S, and 12S) and the mitochondrial protein-coding gene COI. A worldwide sample of ~70 genera representing almost a quarter of generic diversity of the clerid lineage was included and phylogenies were reconstructed using Bayesian and Maximum Likelihood approaches. Results support the monophyly of many proposed subfamilies but were not entirely congruent with either current classification system. The subfamilial relationships within the Cleridae are resolved with support for three main lineages. Tillinae are supported as the sister group to all other subfamilies within the Cleridae, whereas Thaneroclerinae, Korynetinae and a new subfamily formally described here, Epiclininae subf. n, form a sister group to Clerinae + Hydnocerinae.
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Multivariate predictive models are widely used tools for assessment of aquatic ecosystem health and models have been successfully developed for the prediction and assessment of aquatic macroinvertebrates, diatoms, local stream habitat features and fish. We evaluated the ability of a modelling method based on the River InVertebrate Prediction and Classification System (RIVPACS) to accurately predict freshwater fish assemblage composition and assess aquatic ecosystem health in rivers and streams of south-eastern Queensland, Australia. The predictive model was developed, validated and tested in a region of comparatively high environmental variability due to the unpredictable nature of rainfall and river discharge. The model was concluded to provide sufficiently accurate and precise predictions of species composition and was sensitive enough to distinguish test sites impacted by several common types of human disturbance (particularly impacts associated with catchment land use and associated local riparian, in-stream habitat and water quality degradation). The total number of fish species available for prediction was low in comparison to similar applications of multivariate predictive models based on other indicator groups, yet the accuracy and precision of our model was comparable to outcomes from such studies. In addition, our model developed for sites sampled on one occasion and in one season only (winter), was able to accurately predict fish assemblage composition at sites sampled during other seasons and years, provided that they were not subject to unusually extreme environmental conditions (e.g. extended periods of low flow that restricted fish movement or resulted in habitat desiccation and local fish extinctions).
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Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.
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Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.
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We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.
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The New Zealand Threat Classification System (NZTCS) is a national system used to assess the risk of extinction faced by New Zealand plants, animals and fungi. The system is specifically designed to be relevant to New Zealand's unusual ecological and geographic conditions. We undertook a re-evaluation of the status of seven bat taxa based on our knowledge of New Zealand bats using revised NZTCS criteria. Five taxa were listed as Threatened or At Risk: one as Nationally Critical (long-tailed bat Chalinolobus tuberculatus ‘South Island’), one as Nationally Endangered (southern lesser short-tailed bat Mystacina tuberculata tuberculata), two as Nationally Vulnerable (long-tailed bat ‘North Island’ and northern lesser short-tailed bat M. t. aupourica) and one as Declining (central lesser short-tailed bat M. t. rhyacobia). One taxon was assessed as Data Deficient (greater short-tailed bat M. robusta) and one (little red flying fox Pteropus scapulatus) as Vagrant. We suspect declines result primarily from predation and competition from introduced mammals, habitat degradation, and disturbance.
Resumo:
We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.
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Biomechanical analysis of sport performance provides an objective method of determining performance of a particular sporting technique. In particular, it aims to add to the understanding of the mechanisms influencing performance, characterization of athletes, and provide insights into injury predisposition. Whilst the performance in sport of able-bodied athletes is well recognised in the literature, less information and understanding is known on the complexity, constraints and demands placed on the body of an individual with a disability. This paper provides a dialogue that outlines scientific issues of performance analysis of multi-level athletes with a disability, including Paralympians. Four integrated themes are explored the first of which focuses on how biomechanics can contribute to the understanding of sport performance in athletes with a disability and how it may be used as an evidence-based tool. This latter point questions the potential for a possible cultural shift led by emergence of user-friendly instruments. The second theme briefly discusses the role of reliability of sport performance and addresses the debate of two-dimensional and three-dimensional analysis. The third theme address key biomechanical parameters and provides guidance to clinicians, and coaches on the approaches adopted using biomechanical/sport performance analysis for an athlete with a disability starting out, to the emerging and elite Paralympian. For completeness of this discourse, the final theme is based on the controversial issues on the role of assisted devices and the inclusion of Paralympians into able-bodied sport is also presented. All combined, this dialogue highlights the intricate relationship between biomechanics and training of individuals with a disability. Furthermore, it illustrates the complexity of modern training of athletes which can only lead to a better appreciation of the performances to be delivered in the London 2012 Paralympic Games