967 resultados para Habitat quality assessment
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Although genetic diversity is one of the key components of biodiversity, its drivers are still not fully understood. While it is known that genetic diversity is affected both by environmental parameters as well as habitat history, these factors are not often tested together. Therefore, we analyzed 14 microsatellite loci in Abax parallelepipedus, a flightless, forest dwelling ground beetle, from 88 plots in two study regions in Germany. We modeled the effects of historical and environmental variables on allelic richness, and found for one of the regions, the Schorfheide-Chorin, a significant effect of the depth of the litter layer, which is a main component of habitat quality, and of the sampling effort, which serves as an inverse proxy for local population size. For the other region, the Schwäbische Alb, none of the potential drivers showed a significant effect on allelic richness. We conclude that the genetic diversity in our study species is being driven by current local population sizes via environmental variables and not by historical processes in the studied regions. This is also supported by lack of genetic differentiation between local populations sampled from ancient and from recent woodlands. We suggest that the potential effects of former fragmentation and recolonization processes have been mitigated by the large and stable local populations of Abax parallelepipedus in combination with the proximity of the ancient and recent woodlands in the studied landscapes.
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"July 2003"
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Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.
The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.
Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.
An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.
The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.
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Habitat fragmentation can have an impact on a wide variety of biological processes including abundance, life history strategies, mating system, inbreeding and genetic diversity levels of individual species. Although fragmented populations have received much attention, ecological and genetic responses of species to fragmentation have still not been fully resolved. The current study investigated the ecological factors that may influence the demographic and genetic structure of the giant white-tailed rat (Uromys caudimaculatus) within fragmented tropical rainforests. It is the first study to examine relationships between food resources, vegetation attributes and Uromys demography in a quantitative manner. Giant white-tailed rat densities were strongly correlated with specific suites of food resources rather than forest structure or other factors linked to fragmentation (i.e. fragment size). Several demographic parameters including the density of resident adults and juvenile recruitment showed similar patterns. Although data were limited, high quality food resources appear to initiate breeding in female Uromys. Where data were sufficient, influx of juveniles was significantly related to the density of high quality food resources that had fallen in the previous three months. Thus, availability of high quality food resources appear to be more important than either vegetation structure or fragment size in influencing giant white-tailed rat demography. These results support the suggestion that a species’ response to fragmentation can be related to their specific habitat requirements and can vary in response to local ecological conditions. In contrast to demographic data, genetic data revealed a significant negative effect of habitat fragmentation on genetic diversity and effective population size in U. caudimaculatus. All three fragments showed lower levels of allelic richness, number of private alleles and expected heterozygosity compared with the unfragmented continuous rainforest site. Populations at all sites were significantly differentiated, suggesting restricted among population gene flow. The combined effects of reduced genetic diversity, lower effective population size and restricted gene flow suggest that long-term viability of small fragmented populations may be at risk, unless effective management is employed in the future. A diverse range of genetic reproductive behaviours and sex-biased dispersal patterns were evident within U. caudimaculatus populations. Genetic paternity analyses revealed that the major mating system in U. caudimaculatus appeared to be polygyny at sites P1, P3 and C1. Evidence of genetic monogamy, however, was also found in the three fragmented sites, and was the dominant mating system in the remaining low density, small fragment (P2). High variability in reproductive skew and reproductive success was also found but was less pronounced when only resident Uromys were considered. Male body condition predicted which males sired offspring, however, neither body condition nor heterozygosity levels were accurate predictors of the number of offspring assigned to individual males or females. Genetic spatial autocorrelation analyses provided evidence for increased philopatry among females at site P1, but increased philopatry among males at site P3. This suggests that male-biased dispersal occurs at site P1 and female-biased dispersal at site P3, implying that in addition to mating systems, Uromys may also be able to adjust their dispersal behaviour to suit local ecological conditions. This study highlights the importance of examining the mechanisms that underlie population-level responses to habitat fragmentation using a combined ecological and genetic approach. The ecological data suggested that habitat quality (i.e. high quality food resources) rather than habitat quantity (i.e. fragment size) was relatively more important in influencing giant white-tailed rat demographics, at least for the populations studied here . Conversely, genetic data showed strong evidence that Uromys populations were affected adversely by habitat fragmentation and that management of isolated populations may be required for long-term viability of populations within isolated rainforest fragments.
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This paper reviews the means by which teacher quality has been measured. It considers data sources such as students, peers, experts, and examines the psychometrics and scaleproperties of teacher quality assessment instruments with respect to reliability and validity. A list of items for possible inclusion in an elementary student focussed instrument is considered, together with the potential use of such an instrument in measuring teacher quality.
The relationship between clinical outcomes and quality of life for residents of aged care facilities
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Objectives It is widely assumed improving care in residential facilities will improve quality of life (QoL), but little research has explored this relationship. The Clinical Care Indicators (CCI) Tool was developed to fill an existing gap in quality assessment within Australian residential aged care facilities and it was used to explore potential links between clinical outcomes and QoL. Design and Setting Clinical outcome and QoL data were collected within four residential facilities from the same aged care provider. Subjects Subjects were 82 residents of four facilities. Outcome Measures Clinical outcomes were measured using the CCI Tool and QoL data was obtained using the Australian WHOQOL‑100. Results Independent t‑test analyses were calculated to compare individual CCIs with each domain of the WHOQOL‑100, while Pearson’s product moment coefficients (r) were calculated between the total number of problem indicators and QoL scores. Significant results suggested poorer clinical outcomes adversely affected QoL. Social and spiritual QoL were particularly affected by clinical outcomes and poorer status in hydration, falls and depression were most strongly associated with lower QoL scores. Poorer clinical status as a whole was also significantly correlated with poorer QoL. Conclusions Hydration, falls and depression were most often associated with poorer resident QoL and as such appear to be key areas for clinical management in residential aged care. However, poor clinical outcomes overall also adversely affected QoL, which suggests maintaining optimum clinical status through high quality nursing care, would not only be important for resident health but also for enhancing general life quality.
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Residential aged care in Australia does not have a system of quality assessment related to clinical outcomes, creating a significant gap in quality monitoring. Clinical outcomes represent the results of all inputs into care, thus providing an indication of the success of those inputs. To fill this gap, an assessment tool based on resident outcomes (the ResCareQA) was developed and evaluated in collaboration with residential care providers. A useful output of the ResCareQA is a profile of resident clinical status, and this paper will use such outputs to present a snapshot of nine residential facilities. Such comprehensive data has not yet been available within Australia, so this will provide an important insight. ResCareQA data was collected from all residents (N=498) of nine aged care facilities from two major aged care providers. For each facility, numerator–denominator data were calculated to assess the degree of potential clinical problems. Results varied across clinical areas and across facilities, and rank-ordered facility results for selected clinical areas are reviewed and discussed. Use of the ResCareQA to generate clinical outcome data provides a concrete means of monitoring care quality within residential facilities; regular use of the ResCareQA could thus contribute to improved care outcomes within residential aged care.
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Recent years have seen the introduction of formalised accreditation processes in both community and residential aged care, but these only partially address quality assessment within this sector. Residential aged care in Australia does not yet have a standardised system of resident assessment related to clinical, rather than administrative, outcomes. This paper describes the development of a quality assessment tool aimed at addressing this gap. Utilising previous research and the results of nominal groups with experts in the field, the 21-item Clinical Care Indicators (CCI) Tool for residential aged care was developed and trialled nationally. The CCI Tool was found to be simple to use and an effective means of collecting data on the state of resident health and care, with potential benefits for resident care planning and continuous quality improvement within facilities and organisations. The CCI Tool was further refined through a small intervention study to assess its utility as a quality improvement instrument and to investigate its relationship with resident quality of life. The current version covers 23 clinical indicators, takes about 30 minutes to complete and is viewed favourably by nursing staff who use it. Current work focuses on psychometric analysis and benchmarking, which should enable the CCI Tool to make a positive contribution to the measurement of quality in aged care in Australia.
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This paper critiques a 2008 Queensland Studies Authority (QSA) assessment initiative known as Queensland Comparable Assessment Tasks, or QCATs. The rhetoric is that these centrally devised assessment tasks will provide information about how well students can apply what they know, understand and can do in different contexts (QSA, 2009). The QCATs are described as ‘authentic, performance-based assessment’ that involves a ‘meaningful problem’, ‘emphasises critical thinking and reasoning’ and ‘provides students with every opportunity to do their best work’ (QSA, 2009). From my viewpoint as a teacher, I detail my professional concerns with implementing the 2008 middle primary English QCAT in one case study Torres Strait Island community. Specifically I ask ‘QCATs: Comparable with what?’ and ‘QCATs: Whose authentic assessment?’. I predict the possible collateral effects of implementing this English assessment in this remote Indigenous community, concluding, rather than being an example of quality assessment, colloquially speaking, it is nothing more than a ‘dog’.
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PURPOSE. To measure tear film surface quality in healthy and dry eye subjects using three noninvasive techniques of tear film quality assessment and to establish the ability of these noninvasive techniques to predict dry eye. METHODS. Thirty four subjects participated in the study, and were classified as dry eye or normal, based on standard clinical assessments. Three non-invasive techniques were applied for measurement of tear film surface quality: dynamic-area high-speed videokeratoscopy (HSV), wavefront sensing (DWS) and lateral shearing interferometry (LSI). The measurements were performed in both natural blinking conditions (NBC) and in suppressed blinking conditions (SBC). RESULTS. In order to investigate the capability of each method to discriminate dry eye subjects from normal subjects, the receiver operating curve (ROC) was calculated and then the area under the curve (AUC) was extracted. The best result was obtained for the LSI technique (AUC=0.80 in SBC and AUC=0.73 in NBC), which was followed by HSV (AUC=0.72 in SBC and AUC=0.71 in NBC). The best result for DWS was AUC=0.64 obtained for changes in vertical coma in suppressed blinking conditions, while for normal blinking conditions the results were poorer. CONCLUSIONS. Non-invasive techniques of tear film surface assessment can be used for predicting dry eye and this can be achieved in natural blinking as well as suppressed blinking conditions. In this study, LSI showed the best detection performance, closely followed by the dynamic-area HSV. The wavefront sensing technique was less powerful, particularly in natural blinking conditions.
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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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Aim Australian residential aged care does not have a system of quality assessment related to clinical outcomes, or comprehensive quality benchmarking. The Residential Care Quality Assessment was developed to fill this gap; and this paper discusses the process by which preliminary benchmarks representing high and low quality were developed for it. Methods Data were collected from all residents (n = 498) of nine facilities. Numerator–denominator analysis of clinical outcomes occurred at a facility-level, with rank-ordered results circulated to an expert panel. The panel identified threshold scores to indicate excellent and questionable care quality, and refined these through Delphi process. Results Clinical outcomes varied both within and between facilities; agreed thresholds for excellent and poor outcomes were finalised after three Delphi rounds. Conclusion Use of the Residential Care Quality Assessment provides a concrete means of monitoring care quality and allows benchmarking across facilities; its regular use could contribute to improved care outcomes within residential aged care in Australia.
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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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This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.