991 resultados para CART analysis
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This study examined the distribution of major mosquito species and their roles in the transmission of Ross River virus (RRV) infection for coastline and inland areas in Brisbane, Australia (27°28′ S, 153°2′ E). We obtained data on the monthly counts of RRV cases in Brisbane between November 1998 and December 2001 by statistical local areas from the Queensland Department of Health and the monthly mosquito abundance from the Brisbane City Council. Correlation analysis was used to assess the pairwise relationships between mosquito density and the incidence of RRV disease. This study showed that the mosquito abundance of Aedes vigilax (Skuse), Culex annulirostris (Skuse), and Aedes vittiger (Skuse) were significantly associated with the monthly incidence of RRV in the coastline area, whereas Aedes vigilax, Culex annulirostris, and Aedes notoscriptus (Skuse) were significantly associated with the monthly incidence of RRV in the inland area. The results of the classification and regression tree (CART) analysis show that both occurrence and incidence of RRV were influenced by interactions between species in both coastal and inland regions. We found that there was an 89% chance for an occurrence of RRV if the abundance of Ae. vigifax was between 64 and 90 in the coastline region. There was an 80% chance for an occurrence of RRV if the density of Cx. annulirostris was between 53 and 74 in the inland area. The results of this study may have applications as a decision support tool in planning disease control of RRV and other mosquito-borne diseases.
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Background: In Cambodia, malaria transmission is low and most cases occur in forested areas. Seroepidemiological techniques can be used to identify both areas of ongoing transmission and high-risk groups to be targeted by control interventions. This study utilizes repeated cross-sectional data to assess the risk of being malaria sero-positive at two consecutive time points during the rainy season and investigates who is most likely to sero-convert over the transmission season. Methods: In 2005, two cross-sectional surveys, one in the middle and the other at the end of the malaria transmission season, were carried out in two ecologically distinct regions in Cambodia. Parasitological and serological data were collected in four districts. Antibodies to Plasmodium falciparum Glutamate Rich Protein (GLURP) and Plasmodium vivax Merozoite Surface Protein-119 (MSP-119) were detected using Enzyme Linked Immunosorbent Assay (ELISA). The force of infection was estimated using a simple catalytic model fitted using maximum likelihood methods. Risks for sero-converting during the rainy season were analysed using the Classification and Regression Tree (CART) method. Results: A total of 804 individuals participating in both surveys were analysed. The overall parasite prevalence was low (4.6% and 2.0% for P. falciparum and 7.9% and 6.0% for P. vivax in August and November respectively). P. falciparum force of infection was higher in the eastern region and increased between August and November, whilst P. vivax force of infection was higher in the western region and remained similar in both surveys. In the western region, malaria transmission changed very little across the season (for both species). CART analysis for P. falciparum in the east highlighted age, ethnicity, village of residence and forest work as important predictors for malaria exposure during the rainy season. Adults were more likely to increase their antibody responses to P. falciparum during the transmission season than children, whilst members of the Charay ethnic group demonstrated the largest increases. Discussion: In areas of low transmission intensity, such as in Cambodia, the analysis of longitudinal serological data enables a sensitive evaluation of transmission dynamics. Consecutive serological surveys allow an insight into spatio-temporal patterns of malaria transmission. The use of CART enabled multiple interactions to be accounted for simultaneously and permitted risk factors for exposure to be clearly identified.
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Aim Our aim was to discriminate different species of Pinus via pollen analysis in order to assess the responses of particular pine species to orbital and millennial-scale climate changes, particularly during the last glacial period. Location Modern pollen grains were collected from current pine populations along transects from the Pyrenees to southern Iberia and the Balearic Islands. Fossil pine pollen was recovered from the south-western Iberian margin core MD95-2042. Methods We measured a set of morphological traits of modern pollen from the Iberian pine species Pinus nigra, P. sylvestris, P. halepensis, P. pinea and P. pinaster and of fossil pine pollen from selected samples of the last glacial period and the early to mid-Holocene. Classification and regression tree (CART) analysis was used to establish a model from the modern dataset that discriminates pollen from the different pine species and allows identification of fossil pine pollen at the species level. Results The CART model was effective in separating pollen of P. nigra and P. sylvestris from that of the Mediterranean pine group (P. halepensis, P. pinea and P. pinaster). The pollen of Pinus nigra diverged from that of P. sylvestris by having a more flattened corpus. Predictions using this model suggested that fossil pine pollen is mainly from P. nigra in all the samples analysed. Pinus sylvestris was more abundant in samples from Greenland stadials than Heinrich stadials, whereas Mediterranean pines increased in samples from Greenland interstadials and during the early to mid-Holocene. Main conclusions Morphological parameters can be successfully used to increase the taxonomic resolution of fossil pine pollen at the species level for the highland pines (P. nigra and P. sylvestris) and at the group of species level for the Mediterranean pines. Our study indicates that P. nigra was the dominant component of the last glacial south-western/central Iberian pinewoods, although the species composition of these woodlands varied in response to abrupt climate changes.
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Thesis (Master's)--University of Washington, 2016-06
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Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.
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An engineering analysis of the design of two-wheel bullock carts has been carried out with the aid of a mathematical model. Non-dimensional expressions for the pull and the neck load have been developed. In the first instance, the cart is assumed to be cruising at constant velocity on a terrain with the effective coefficient of rolling friction varying over a wide range (0.001 to 0.5) and the gradient varying between +0.2 to −0.2. Subsequently, the effect of inertia force due to an acceleration parallel to the ground is studied. In the light of this analysis, two modifications to the design of the cart have been proposed and the relative merits of the current designs and the proposed designs are discussed.
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Purpose: This study explored the spatial distribution of notified cryptosporidiosis cases and identified major socioeconomic factors associated with the transmission of cryptosporidiosis in Brisbane, Australia. Methods: We obtained the computerized data sets on the notified cryptosporidiosis cases and their key socioeconomic factors by statistical local area (SLA) in Brisbane for the period of 1996 to 2004 from the Queensland Department of Health and Australian Bureau of Statistics, respectively. We used spatial empirical Bayes rates smoothing to estimate the spatial distribution of cryptosporidiosis cases. A spatial classification and regression tree (CART) model was developed to explore the relationship between socioeconomic factors and the incidence rates of cryptosporidiosis. Results: Spatial empirical Bayes analysis reveals that the cryptosporidiosis infections were primarily concentrated in the northwest and southeast of Brisbane. A spatial CART model shows that the relative risk for cryptosporidiosis transmission was 2.4 when the value of the social economic index for areas (SEIFA) was over 1028 and the proportion of residents with low educational attainment in an SLA exceeded 8.8%. Conclusions: There was remarkable variation in spatial distribution of cryptosporidiosis infections in Brisbane. Spatial pattern of cryptosporidiosis seems to be associated with SEIFA and the proportion of residents with low education attainment.
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The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...
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Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.
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Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.
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A review of future management arrangements for the Queensland East Coast Trawl fishery was undertaken in 2010 to develop a management plan for the next 10 years. A key question raised at the start of the review process was: what should the management plan achieve? As with fisheries management in most countries, multiple management objectives were implicit in policy statements, but were poorly specified in some areas (particularly social objectives) and strongly identified in others (e.g., an objective of sustainability). As a start to the management review process, an analysis of what objectives the management system should aim to achieve was undertaken. A review of natural resource management objectives employed internationally was used to develop a candidate list, and the objectives most relevant to the fishery were short-listed by a scientific advisory group. Additional objectives specific to Queensland fisheries management, but not identified in the international review, were also identified and incorporated into the objective set. The relative importance of the different objectives to different stakeholder groups was assessed using the Analytic Hierarchy Process. As with other studies, the relative importance of the different objectives varied both within and between the different stakeholder groups, although general trends in preferences were observed.
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La version intégrale de cette thèse est disponible uniquement pour consultation individuelle à la Bibliothèque de musique de l’Université de Montréal (www.bib.umontreal.ca/MU).
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Le suivi thérapeutique est recommandé pour l’ajustement de la dose des agents immunosuppresseurs. La pertinence de l’utilisation de la surface sous la courbe (SSC) comme biomarqueur dans l’exercice du suivi thérapeutique de la cyclosporine (CsA) dans la transplantation des cellules souches hématopoïétiques est soutenue par un nombre croissant d’études. Cependant, pour des raisons intrinsèques à la méthode de calcul de la SSC, son utilisation en milieu clinique n’est pas pratique. Les stratégies d’échantillonnage limitées, basées sur des approches de régression (R-LSS) ou des approches Bayésiennes (B-LSS), représentent des alternatives pratiques pour une estimation satisfaisante de la SSC. Cependant, pour une application efficace de ces méthodologies, leur conception doit accommoder la réalité clinique, notamment en requérant un nombre minimal de concentrations échelonnées sur une courte durée d’échantillonnage. De plus, une attention particulière devrait être accordée à assurer leur développement et validation adéquates. Il est aussi important de mentionner que l’irrégularité dans le temps de la collecte des échantillons sanguins peut avoir un impact non-négligeable sur la performance prédictive des R-LSS. Or, à ce jour, cet impact n’a fait l’objet d’aucune étude. Cette thèse de doctorat se penche sur ces problématiques afin de permettre une estimation précise et pratique de la SSC. Ces études ont été effectuées dans le cadre de l’utilisation de la CsA chez des patients pédiatriques ayant subi une greffe de cellules souches hématopoïétiques. D’abord, des approches de régression multiple ainsi que d’analyse pharmacocinétique de population (Pop-PK) ont été utilisées de façon constructive afin de développer et de valider adéquatement des LSS. Ensuite, plusieurs modèles Pop-PK ont été évalués, tout en gardant à l’esprit leur utilisation prévue dans le contexte de l’estimation de la SSC. Aussi, la performance des B-LSS ciblant différentes versions de SSC a également été étudiée. Enfin, l’impact des écarts entre les temps d’échantillonnage sanguins réels et les temps nominaux planifiés, sur la performance de prédiction des R-LSS a été quantifié en utilisant une approche de simulation qui considère des scénarios diversifiés et réalistes représentant des erreurs potentielles dans la cédule des échantillons sanguins. Ainsi, cette étude a d’abord conduit au développement de R-LSS et B-LSS ayant une performance clinique satisfaisante, et qui sont pratiques puisqu’elles impliquent 4 points d’échantillonnage ou moins obtenus dans les 4 heures post-dose. Une fois l’analyse Pop-PK effectuée, un modèle structural à deux compartiments avec un temps de délai a été retenu. Cependant, le modèle final - notamment avec covariables - n’a pas amélioré la performance des B-LSS comparativement aux modèles structuraux (sans covariables). En outre, nous avons démontré que les B-LSS exhibent une meilleure performance pour la SSC dérivée des concentrations simulées qui excluent les erreurs résiduelles, que nous avons nommée « underlying AUC », comparée à la SSC observée qui est directement calculée à partir des concentrations mesurées. Enfin, nos résultats ont prouvé que l’irrégularité des temps de la collecte des échantillons sanguins a un impact important sur la performance prédictive des R-LSS; cet impact est en fonction du nombre des échantillons requis, mais encore davantage en fonction de la durée du processus d’échantillonnage impliqué. Nous avons aussi mis en évidence que les erreurs d’échantillonnage commises aux moments où la concentration change rapidement sont celles qui affectent le plus le pouvoir prédictif des R-LSS. Plus intéressant, nous avons mis en exergue que même si différentes R-LSS peuvent avoir des performances similaires lorsque basées sur des temps nominaux, leurs tolérances aux erreurs des temps d’échantillonnage peuvent largement différer. En fait, une considération adéquate de l'impact de ces erreurs peut conduire à une sélection et une utilisation plus fiables des R-LSS. Par une investigation approfondie de différents aspects sous-jacents aux stratégies d’échantillonnages limités, cette thèse a pu fournir des améliorations méthodologiques notables, et proposer de nouvelles voies pour assurer leur utilisation de façon fiable et informée, tout en favorisant leur adéquation à la pratique clinique.
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Combination Antiretroviral Therapy (cART) aims to inhibit viral replication, delay immunodeficiency progression and improve survival in AIDS patients. The objective of this study was to compare two different schemes of cART, based on plasma viral load (VL) and CD4+ T lymphocyte count, during 48 weeks of treatment. For this purpose, 472 medical charts of a Specialized Outpatient Service were reviewed from 1998 to 2005. Out of these, 58 AIDS patients who had received a triple drug scheme as the initial treatment were included in the study and two groups were formed: Group 1 (G1): 47 individuals treated with two nucleoside reverse-transcriptase inhibitors (NRTI) and one non-nucleoside reverse-transcriptase inhibitor; Group 2 (G2): 11 patients treated with two NRTI and one protease inhibitor. In G1 and G2, 53.2% and 81.8% respectively were patients with an AIDS-defining disease. The T CD4+ lymphocyte count increased progressively up until the 24th week of treatment in all patients, while VL became undetectable in 68.1% of G1 and in 63.6% of G2. The study concluded that the evolutions of laboratory tests were similar in the two treatment groups and that both presented a favorable clinical evolution.
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Esta dissertação trata de uma análise sobre as estratégias de pequenos produtores rurais organizados em cooperativas na busca da garantia de trabalho e renda, no município de Cametá, Pará. De tal modo, considerou-se, inicialmente, as influências pelas condições de inserção social, produtiva e econômica e o incentivo pela Prelazia e instituições de assessoria que reforçam essa organização. Nesse trajeto, o Sindicato de Trabalhadores (as) Rurais motivaram lutas reivindicatórias para a melhoria das condições socioeconômicas locais em Cametá. As reflexões teóricas e a realidade prática, desses autores, mostram que as relações de promoção vêm sendo articuladas na perspectiva das transformações que tem impactado esse município, as quais foram agravadas desde a implantação dos grandes projetos na Amazônia, a exemplo da implantação da Hidrelétrica de Tucuruí, que alterou significativamente o modo de vida dessa população. Dessa forma, os trabalhadores rurais, organizados coletivamente, passaram a atuar pela superação dessas dificuldades, através de atividades produtivas como estratégia de desenvolvimento local sustentável, evidenciando a garantia de instrumentos para a produção e comercialização de frutos, com ênfase no açaí, mas também em outros produtos como a farinha de mandioca e recentemente as sementes oleaginosas. Portanto, desenvolve-se uma caracterização sócio-produtiva de Cametá, analisa-se o surgimento do STR - Cametá, a criação da CART, particularizando sua relação às estratégias de comercialização em rede por meio da organização do Consórcio de Comercialização e da Federação das Cooperativas da Agricultura Familiar e Economia Solidária - FECAFES como instrumento de valorização produtiva estratégica à organização dos pequenos produtores rurais de Cametá.