O presente trabalho é um esforço metodológico ao tentar aplicar um modelo arqueológico preditivo em sítios do Amapá conhecidos como Alinhamentos de Pedra. Após serem feitas as análises de documentos históricos da década de 1920 e das pesquisas realizadas na década de 1940, juntamente com os levantamentos feitos pelo Museu Goeldi em 2005, foi possível testar em campo o modelo preditivo proposto. Para a sua construção foram utilizadas também as discussões sobre os processos de formação do registro arqueológico e o teste de hipóteses já levantadas sobre estes sítios oriundas desde as primeiras pesquisas em fins do século XIX. Os resultados alcançados, apesar de incipientes, permitiram um panorama da história da arqueologia amazônica e a avaliação que o uso de tecnologias como o Sistema de Informação Geográfica (SIG) podem trazer como resultados positivos para a pesquisa arqueológica na região. / This work is a methodological effort to apply an Archaeological Predictive Model on sites known as Stone Alignments at the State of Amapá-Brazil. After some analyses of historical documents from the 1920\'s and 1940\'s, and the last surveys realized by Goeldi Museum in 2005, was possible to test empirically the predictive model. To its construction were used the discussions on site formation processes and the use of previous hypotheses created since the end of the XIX century. The results achieved allowed a brief view on the history of Amazon archaeology and the evaluation of technologies as the Geographical Information System (GIS) as a positive archaeological tool to produce researches in the region.

Introduction Treating localized prostate cancer with combination radiotherapy consisting ofexternal beam radiotherapy (EBRT) and high-dose-rate brachytherapy (HDR-BT) has beenproven to result in better disease outcome than EBRT only. There is, however, a decreasingtrend in utilization of combination therapy, partially due to concerns for elevated toxicityrisks. Aim To determine which parameters correlate to acute and late (≤ 6 months) urinary toxicity(AUT and LUT) and acute and late rectal toxicity (ART and LRT), and thereafter createpredictive models for rectal toxicity. Methods Data on toxicity rates and 32 patient, tumor and treatment parameters were collectedfrom 359 patients treated between 2008 and 2018 with EBRT (42 Gy in 14 fractions) andHDR-BT (14.5 Gy in 1 fraction) for localized prostate cancer at Örebro University Hospital.Bivariate analyses were conducted on all parameters and the outcome variables AUT, LUT,ART and LRT grade ≥ 1, graded according to the RTOG-criteria. Parameters correlating toART and LRT in this and previous studies were included in multivariate logistic regressionanalyses for creation of predictive models. Results Most toxicities, 86%, were of grade 0 or 1, only 9% of patients had grade 2 – 3toxicity. Only 2 – 4 parameters correlated to the respective toxicities in bivariate analyses.Logistic regressions generated no significant predictors of ART or LRT. Therefore, nopredictive models were obtained. Conclusion None of the included parameters have enough discriminative abilities regardingrectal toxicity. Predictive models can most probably be obtained by including otherparameters and more patients.

Oil production from EOR and waterflood processes supplies a considerable amount of the world's oil production. Therefore, the screening and selection of the best EOR process becomes important. Numerous steps are involved in evaluating EOR methods for field applications. Binary screening guides in which reservoirs are selected on the basis of reservoir average rock and fluid properties are consulted for initial determination of applicability. However, quick quantitative comparisons and performance predictions of EOR processes are more complicated and important than binary screening that are the objectives of EOR forecasting. Forecasting (predicting) the performance of EOR processes plays an important role in the study, design and selection of the best method for a particular reservoir or a collection of reservoirs. In EOR forecasting, we look for finding ways to get quick quantitative results of the performance of different EOR processes using analytical model/s before detailed numerical simulations of the reservoirs under study. Although numerical simulation of the reservoirs is widely used, there are significant obstacles that restrict its applicability. Lack of necessary reservoir data and time consuming computations and analyses can be barriers even for history matching and/or predicting EOR/waterflood performance of one reservoir. There are different forecasting (predictive) models for evaluation of different secondary/tertiary recovery methods. However, lack of a general purpose EOR/waterflood forecasting model is unsatisfactory because any differences in results can be caused by differences in the model rather than differences in the processes. As the main objective of this study, we address this deficiency by presenting a novel and robust analytical-base general EOR and waterflood forecasting model/tool (UTF) that does not rely on conventional numerical simulation. The UTF conceptual model is based on the fundamental law of material balance, segregated flow and fractional flux theories and is applied for both history matching and forecasting the EOR/waterflood processes. The forecasting model generates the key results of isothermal EOR and waterflooding processes including variations of average oil saturation, recovery efficiency, volumetric sweep efficiency, oil cut and oil rate with real or dimensionless time. The forecasting model was validated against field data and numerical simulation results for isothermal EOR and waterflooding processes. The forecasting model reproduced well (R2> 0.8) all of the field data and reproduced the simulated data even better. To develop the UTF for forecasting when there is no injection/production history data, we used experimental design and numerical simulation and successfully generated the in-situ correlations (response surfaces) of the forecasting model variables. The forecasting model variables were proven to be well correlated to reservoir/recovery process variables and can be reliably used for forecasting. As an extension to the abilities of the forecasting model, these correlations were used for prediction of volumetric sweep efficiency and missing/dynamic pore volume of EOR and waterflooding processes. / text

Invasive alien species (IAS) pose a serious threat to ecosystems and societies worldwide. Local ecological knowledge (LEK) is increasingly valued as a means of understanding environmental issues; however, its application in the context of IAS research has been limited. The overall objective of this study was to document the LEK of farmers and Weed Supervisors to gain insight into a recent IAS, Odontites serotina. I conducted semi-structured interviews with farmers and Weed Supervisors with O. serotina management experience. Results indicated that the socio-economic impacts for farmers were severe in affected rural communities. However, participants had developed promising control techniques, including the application of compost mulch. I used this LEK as well as data on species occurrence, environmental variables, and measures of propagule pressure to forecast the potential distribution of O. serotina across Manitoba. The risk map generated will be useful for guiding future monitoring and public outreach efforts.

Invasive alien species (IAS) pose a serious threat to ecosystems and societies worldwide. Local ecological knowledge (LEK) is increasingly valued as a means of understanding environmental issues; however, its application in the context of IAS research has been limited. The overall objective of this study was to document the LEK of farmers and Weed Supervisors to gain insight into a recent IAS, Odontites serotina. I conducted semi-structured interviews with farmers and Weed Supervisors with O. serotina management experience. Results indicated that the socio-economic impacts for farmers were severe in affected rural communities. However, participants had developed promising control techniques, including the application of compost mulch. I used this LEK as well as data on species occurrence, environmental variables, and measures of propagule pressure to forecast the potential distribution of O. serotina across Manitoba. The risk map generated will be useful for guiding future monitoring and public outreach efforts.

Irradiation with ultraviolet (UV) light is used for the disinfection of bacterial contaminants in the production of potable water, and in the treatment of selected wastewaters. However, efficacy of UV disinfection is limited by the combined effect of suspended solids concentration and UV absorbance. Limited published UV disinfection data are available that account for the combined effects of UV dose, suspended solids concentration and UV absorbance. This present lack of a rigorous quantitative understanding of the kinetics of UV disinfection limits process optimisation and wider application of UV treatment. The development and validation of an adequate model to describe UV disinfection kinetics presented in this thesis can therefore be justified by an increased confidence of reliability of design for UV disinfection. Using the published data of Nguyen (1999), four established model forms were assessed to account for the combined effect of suspended solids and/or soluble UV absorbing compounds, and UV dose on the efficacy of disinfection. The four model forms were: a log-linear form, Davey Linear-Arrhenius (DL-A), Square-Root (or Ratkowsky- Belehradek) and a general nth order Polynomial (nOP) form that was limited to a third order. Criteria for assessment of an adequate predictive model were established including: accuracy of predicted against observed values, percent variance accounted for (%V), and; appraisal of residuals. The DL-A model was shown to best fit the data for UV disinfection of Escherichia coli (ATCC 25922); followed by the nOP, log-linear and Square-Root forms. However, the DL-A form must be used in conjunction with a first-order chemical reaction equation, and was shown to predict poorly at high experimental values of UV dose (> 40,000 μWs cm-2). The DL-A model was not amenable to extrapolation beyond the observed UV dose range. To overcome the shortcomings of the Davey Linear-Arrhenius model synthesis of two new, non-linear model forms was undertaken. The two models were a modified exponentially damped polynomial (EDPm) and a form based on the Weibull probability distribution. The EDPm model has three terms: a rate coefficient (k), a damping coefficient (λ), and; a breakpoint dose ([dose]B). The rate coefficient governs the initial rate of disinfection prior to the onset of tailing, whilst the breakpoint is the UV dose that indicates the onset of tailing. The damping coefficient controls curvature in the survivor curve. The Weibull model has just two terms: a dimensionless scale parameter (β0), and; a shape parameter (β1). The scale parameter represents the level of disinfection in the tail of the survivor curve (as log10 N/N0), whilst the shape parameter governs the degree of curvature of the survivor data. Each model was assessed against the independent and published UV disinfection data of Nelson (2000) for treatment of faecal coliforms in a range of waste stabilisation pond effluents. Both models were found to be well suited to account for tailing in these UV disinfection data. Overall, the EDPm model gave a better fit to the data than the Weibull model form. To rigorously validate the suitability of the new EDPm and Weibull models a series of experimental trials were designed and carried out in a small-scale pilot UV disinfection unit. These trials included data determined specifically at low values of UV dose (<10,000 μWs cm-2) to fill the gap in the experimental data of Nguyen (1999). The experimental trials were carried out using a commercially available, UV disinfection unit (LC5TM from Ultraviolet Technology of Australasia Pty Ltd). Purified water contaminated with Escherichia coli (ATCC 25922) with a range of feed water flow rates (1 to 4 L min-1) was used. E. coli was selected because it is found in sewage, or water contaminated with faecal material, and is used as an indicator for the presence of enteric pathogens. E. coli should not be present in potable water. The hydrodynamics of water flow within the disinfection unit were established using digital video photography of dye trace studies with Methylene Blue. Nominal UV dose (2,700 to 44,200 μWs cm-2) was controlled by manipulating the flow rate of feed water through the UV disinfection unit (i.e. residence time), or by varying the exposed length of the control volume of the disinfection unit. The transmittance of the feed water (at 254 nm) was adjusted by the addition of either a soluble UV absorbing agent (International RoastTM instant coffee powder; 0.001 to 0.07 g L-1), or by addition of suspended matter as diatomaceous earth (Celite 503TM; 0.1 to 0.7 g L-1, with a median particle size of 23 μm). The absorbing agent (instant coffee), when in a comparable concentration, was found to produce a greater reduction in water transmission than the suspended material (Celite 503TM). It therefore contributed to a greater reduction in the initial rate of disinfection. Neither agent was found to produce a systematic reduction in the observed efficacy of disinfection however. Experimental results highlight that in the absence of soluble absorbing agents, or suspended solids, the initial rate of disinfection is higher when fewer viable bacteria are initially present. Both the new EDPm and Weibull forms gave a good fit to the experimental data. The EDPm better fitted the data on the basis of residual sum-of-squares (0.03 to 2.13 for EDPm cf. 0.16 to 4.37 for the Weibull form). These models are both of a form suitable for practical use in modelling UV disinfection data. Results of this research highlight the impact of water quality, as influenced by the combined effect of UV dose, suspended solids concentration and UV absorbance, on small-scale UV disinfection for potable water production. Importantly, results show that the concentration of soluble UV absorbing agents and suspended solids are not in themselves sufficient criteria on which to base assessment of efficacy of UV disinfection / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1342403 / Thesis (M.Eng.Sc.) - University of Adelaide, School of Chemical Engineering, 2008

Irradiation with ultraviolet (UV) light is used for the disinfection of bacterial contaminants in the production of potable water, and in the treatment of selected wastewaters. However, efficacy of UV disinfection is limited by the combined effect of suspended solids concentration and UV absorbance. Limited published UV disinfection data are available that account for the combined effects of UV dose, suspended solids concentration and UV absorbance. This present lack of a rigorous quantitative understanding of the kinetics of UV disinfection limits process optimisation and wider application of UV treatment. The development and validation of an adequate model to describe UV disinfection kinetics presented in this thesis can therefore be justified by an increased confidence of reliability of design for UV disinfection. Using the published data of Nguyen (1999), four established model forms were assessed to account for the combined effect of suspended solids and/or soluble UV absorbing compounds, and UV dose on the efficacy of disinfection. The four model forms were: a log-linear form, Davey Linear-Arrhenius (DL-A), Square-Root (or Ratkowsky- Belehradek) and a general nth order Polynomial (nOP) form that was limited to a third order. Criteria for assessment of an adequate predictive model were established including: accuracy of predicted against observed values, percent variance accounted for (%V), and; appraisal of residuals. The DL-A model was shown to best fit the data for UV disinfection of Escherichia coli (ATCC 25922); followed by the nOP, log-linear and Square-Root forms. However, the DL-A form must be used in conjunction with a first-order chemical reaction equation, and was shown to predict poorly at high experimental values of UV dose (> 40,000 μWs cm-2). The DL-A model was not amenable to extrapolation beyond the observed UV dose range. To overcome the shortcomings of the Davey Linear-Arrhenius model synthesis of two new, non-linear model forms was undertaken. The two models were a modified exponentially damped polynomial (EDPm) and a form based on the Weibull probability distribution. The EDPm model has three terms: a rate coefficient (k), a damping coefficient (λ), and; a breakpoint dose ([dose]B). The rate coefficient governs the initial rate of disinfection prior to the onset of tailing, whilst the breakpoint is the UV dose that indicates the onset of tailing. The damping coefficient controls curvature in the survivor curve. The Weibull model has just two terms: a dimensionless scale parameter (β0), and; a shape parameter (β1). The scale parameter represents the level of disinfection in the tail of the survivor curve (as log10 N/N0), whilst the shape parameter governs the degree of curvature of the survivor data. Each model was assessed against the independent and published UV disinfection data of Nelson (2000) for treatment of faecal coliforms in a range of waste stabilisation pond effluents. Both models were found to be well suited to account for tailing in these UV disinfection data. Overall, the EDPm model gave a better fit to the data than the Weibull model form. To rigorously validate the suitability of the new EDPm and Weibull models a series of experimental trials were designed and carried out in a small-scale pilot UV disinfection unit. These trials included data determined specifically at low values of UV dose (<10,000 μWs cm-2) to fill the gap in the experimental data of Nguyen (1999). The experimental trials were carried out using a commercially available, UV disinfection unit (LC5TM from Ultraviolet Technology of Australasia Pty Ltd). Purified water contaminated with Escherichia coli (ATCC 25922) with a range of feed water flow rates (1 to 4 L min-1) was used. E. coli was selected because it is found in sewage, or water contaminated with faecal material, and is used as an indicator for the presence of enteric pathogens. E. coli should not be present in potable water. The hydrodynamics of water flow within the disinfection unit were established using digital video photography of dye trace studies with Methylene Blue. Nominal UV dose (2,700 to 44,200 μWs cm-2) was controlled by manipulating the flow rate of feed water through the UV disinfection unit (i.e. residence time), or by varying the exposed length of the control volume of the disinfection unit. The transmittance of the feed water (at 254 nm) was adjusted by the addition of either a soluble UV absorbing agent (International RoastTM instant coffee powder; 0.001 to 0.07 g L-1), or by addition of suspended matter as diatomaceous earth (Celite 503TM; 0.1 to 0.7 g L-1, with a median particle size of 23 μm). The absorbing agent (instant coffee), when in a comparable concentration, was found to produce a greater reduction in water transmission than the suspended material (Celite 503TM). It therefore contributed to a greater reduction in the initial rate of disinfection. Neither agent was found to produce a systematic reduction in the observed efficacy of disinfection however. Experimental results highlight that in the absence of soluble absorbing agents, or suspended solids, the initial rate of disinfection is higher when fewer viable bacteria are initially present. Both the new EDPm and Weibull forms gave a good fit to the experimental data. The EDPm better fitted the data on the basis of residual sum-of-squares (0.03 to 2.13 for EDPm cf. 0.16 to 4.37 for the Weibull form). These models are both of a form suitable for practical use in modelling UV disinfection data. Results of this research highlight the impact of water quality, as influenced by the combined effect of UV dose, suspended solids concentration and UV absorbance, on small-scale UV disinfection for potable water production. Importantly, results show that the concentration of soluble UV absorbing agents and suspended solids are not in themselves sufficient criteria on which to base assessment of efficacy of UV disinfection / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1342403 / Thesis (M.Eng.Sc.) - University of Adelaide, School of Chemical Engineering, 2008

Irradiation with ultraviolet (UV) light is used for the disinfection of bacterial contaminants in the production of potable water, and in the treatment of selected wastewaters. However, efficacy of UV disinfection is limited by the combined effect of suspended solids concentration and UV absorbance. Limited published UV disinfection data are available that account for the combined effects of UV dose, suspended solids concentration and UV absorbance. This present lack of a rigorous quantitative understanding of the kinetics of UV disinfection limits process optimisation and wider application of UV treatment. The development and validation of an adequate model to describe UV disinfection kinetics presented in this thesis can therefore be justified by an increased confidence of reliability of design for UV disinfection. Using the published data of Nguyen (1999), four established model forms were assessed to account for the combined effect of suspended solids and/or soluble UV absorbing compounds, and UV dose on the efficacy of disinfection. The four model forms were: a log-linear form, Davey Linear-Arrhenius (DL-A), Square-Root (or Ratkowsky- Belehradek) and a general nth order Polynomial (nOP) form that was limited to a third order. Criteria for assessment of an adequate predictive model were established including: accuracy of predicted against observed values, percent variance accounted for (%V), and; appraisal of residuals. The DL-A model was shown to best fit the data for UV disinfection of Escherichia coli (ATCC 25922); followed by the nOP, log-linear and Square-Root forms. However, the DL-A form must be used in conjunction with a first-order chemical reaction equation, and was shown to predict poorly at high experimental values of UV dose (> 40,000 μWs cm-2). The DL-A model was not amenable to extrapolation beyond the observed UV dose range. To overcome the shortcomings of the Davey Linear-Arrhenius model synthesis of two new, non-linear model forms was undertaken. The two models were a modified exponentially damped polynomial (EDPm) and a form based on the Weibull probability distribution. The EDPm model has three terms: a rate coefficient (k), a damping coefficient (λ), and; a breakpoint dose ([dose]B). The rate coefficient governs the initial rate of disinfection prior to the onset of tailing, whilst the breakpoint is the UV dose that indicates the onset of tailing. The damping coefficient controls curvature in the survivor curve. The Weibull model has just two terms: a dimensionless scale parameter (β0), and; a shape parameter (β1). The scale parameter represents the level of disinfection in the tail of the survivor curve (as log10 N/N0), whilst the shape parameter governs the degree of curvature of the survivor data. Each model was assessed against the independent and published UV disinfection data of Nelson (2000) for treatment of faecal coliforms in a range of waste stabilisation pond effluents. Both models were found to be well suited to account for tailing in these UV disinfection data. Overall, the EDPm model gave a better fit to the data than the Weibull model form. To rigorously validate the suitability of the new EDPm and Weibull models a series of experimental trials were designed and carried out in a small-scale pilot UV disinfection unit. These trials included data determined specifically at low values of UV dose (<10,000 μWs cm-2) to fill the gap in the experimental data of Nguyen (1999). The experimental trials were carried out using a commercially available, UV disinfection unit (LC5TM from Ultraviolet Technology of Australasia Pty Ltd). Purified water contaminated with Escherichia coli (ATCC 25922) with a range of feed water flow rates (1 to 4 L min-1) was used. E. coli was selected because it is found in sewage, or water contaminated with faecal material, and is used as an indicator for the presence of enteric pathogens. E. coli should not be present in potable water. The hydrodynamics of water flow within the disinfection unit were established using digital video photography of dye trace studies with Methylene Blue. Nominal UV dose (2,700 to 44,200 μWs cm-2) was controlled by manipulating the flow rate of feed water through the UV disinfection unit (i.e. residence time), or by varying the exposed length of the control volume of the disinfection unit. The transmittance of the feed water (at 254 nm) was adjusted by the addition of either a soluble UV absorbing agent (International RoastTM instant coffee powder; 0.001 to 0.07 g L-1), or by addition of suspended matter as diatomaceous earth (Celite 503TM; 0.1 to 0.7 g L-1, with a median particle size of 23 μm). The absorbing agent (instant coffee), when in a comparable concentration, was found to produce a greater reduction in water transmission than the suspended material (Celite 503TM). It therefore contributed to a greater reduction in the initial rate of disinfection. Neither agent was found to produce a systematic reduction in the observed efficacy of disinfection however. Experimental results highlight that in the absence of soluble absorbing agents, or suspended solids, the initial rate of disinfection is higher when fewer viable bacteria are initially present. Both the new EDPm and Weibull forms gave a good fit to the experimental data. The EDPm better fitted the data on the basis of residual sum-of-squares (0.03 to 2.13 for EDPm cf. 0.16 to 4.37 for the Weibull form). These models are both of a form suitable for practical use in modelling UV disinfection data. Results of this research highlight the impact of water quality, as influenced by the combined effect of UV dose, suspended solids concentration and UV absorbance, on small-scale UV disinfection for potable water production. Importantly, results show that the concentration of soluble UV absorbing agents and suspended solids are not in themselves sufficient criteria on which to base assessment of efficacy of UV disinfection / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1342403 / Thesis (M.Eng.Sc.) - University of Adelaide, School of Chemical Engineering, 2008

A leishmaniose visceral americana (LVA) é uma doença em expansão no Brasil, para a qual se dispõem de poucas, e aparentemente ineficientes, estratégias de controle. Um dos grandes problemas para a contenção da leishmaniose visceral americana é a falta de um método acurado de identificação dos cães infectados, considerados os principais reservatórios da doença no meio urbano. Neste sentido, a caracterização de marcadores clínico-laboratoriais da infecção neste reservatório e a avaliação mais adequada do desempenho de testes para diagnóstico da infecção podem contribuir para aumentar a efetividade das estratégias de controle da LVA. Com isso, o presente estudo tem dois objetivos principais: (1) desenvolver e validar um modelo de predição para o parasitismo por Leishmania chagasi em cães, baseado em resultados de testes sorológicos e sinais clínicos e (2) avaliar a sensibilidade e especificidade de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por L. chagasi mediante análise de classe latente. O primeiro objetivo foi desenvolvido a partir de estudo em que foram obtidos dados de exames clínico, sorológico e parasitológico de todos os cães, suspeitos ou não de LVA, atendidos no Hospital Veterinário Universitário da Universidade Federal do Piauí (HVU-UFPI), em Teresina, nos anos de 2003 e 2004, totalizando 1412 animais. Modelos de regressão logística foram construídos com os animais atendidos em 2003 com a finalidade de desenvolver um modelo preditivo para o parasitismo com base nos sinais clínicos e resultados de sorologia por Imunofluorescência Indireta (IFI). Este modelo foi validado nos cães atendidos no hospital em 2004. Para a avaliação da área abaixo da curva ROC (auROC), sensibilidade, especificidade, valores preditivos positivo (VPP), valores preditivos negativo (VPN) e acurácia global, foram criados três modelos: um somente baseado nas variáveis clínicas, outro considerando somente o resultado sorológico e um último considerando conjuntamente a clínica e a sorologia. Dentre os três, o último modelo apresentou o melhor desempenho (auROC=90,1%, sensibilidade=82,4%, especificidade=81,6%, VPP=73,4%, VPN=88,2% e acurácia global=81,9%). Conclui-se que o uso de modelos preditivos baseados em critérios clínicos e sorológicos para o diagnóstico da leishmaniose visceral canina pode ser de utilidade no processo de avaliação da infecção canina, promovendo maior agilidade na contenção destes animais com a finalidade de reduzir os níveis de transmissão. O segundo objetivo foi desenvolvido por meio de um estudo transversal com 715 cães de idade entre 1 mês e 13 anos, com raça variada avaliados por clínicos veterinários no HVU-UFPI, no período de janeiro a dezembro de 2003. As sensibilidades e especificidades de critérios clínicos, sorológicos e parasitológicos para detecção de infecção canina por Leishmania chagasi foram estimadas por meio de análise de classe latente, considerando quatro modelos de testes e diferentes pontos de corte. As melhores sensibilidades estimadas para os critérios clínico, sorológico e parasitológico foram de 60%, 95% e 66%, respectivamente. Já as melhores especificidades estimadas para os critérios clínico, sorológico e parasitológico foram de 77%, 90% e 100%, respectivamente. Conclui-se que o uso do exame parasitológico como padrão-ouro para validação de testes diagnósticos não é apropriado e que os indicadores de acurácia dos testes avaliados são insuficientes e não justificam que eles sejam usados isoladamente para diagnóstico da infecção com a finalidade de controle da doença. / American visceral leishmaniasis (AVL) is an expanding disease in Brazil, for which few, and apparently inefficient, control strategies are available. A major problem for the containment of visceral leishmaniasis is the lack of an accurate test for the identification of infected dogs, which are considered the main reservoirs of the disease in urban areas. In this sense, the characterization of clinical and laboratory markers of the infection in this reservoir, as well as, a more appropriate assessment of the performance of tests for the diagnosis of infection, might increase the effectiveness of control strategies for AVL. Thus, this study has two main objectives: (1) to develop and validate a prediction model for parasitism by Leishmania chagasi in dogs, based on the results of serological tests and clinical signs and (2) to evaluate the sensitivity and specificity of a clinical criterion, and of parasitological and serological tests for canine infection by L. chagasi using latent class analysis. The first goal was developed from a study in which clinical, serological and parasitological data were obtained for all dogs, suspicious or not to AVL, admitted at the Veterinary Hospital at the Federal University of Piauí, Teresina, in the years of 2003 and 2004, totaling 1412 animals. Logistic regression models were constructed with the animals admitted in 2003 with the aim of developing a predictive model for parasitism based on clinical signs and results of serology by indirect immunofluorescence (IIF). This model was validated in dogs admitted at the hospital in 2004. To evaluate the area under the ROC curve (AuROC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall accuracy, three models were developed: one based only on clinical variables, other only with the serological results and a final model based on both the clinical and serological data. Among the three, the last model showed the best performance (AuROC=90.1%, sensitivity 82.4%, specificity=81.6%, PPV=73.4% NPV=88.2% and overall accuracy=81.9%). It is concluded that the use of predictive models based on clinical and serological data for diagnosis of canine visceral leishmaniasis might be useful in the evaluation of canine infection, allowing the anticipation of ontainment of these animals in order to reduce transmission levels. The second goal was developed through a cross-sectional study of 715 dogs aged between 1 month and 13 years, with varied races evaluated by veterinarians at VUH-UFPI in the period January to December 2003. The sensitivities and specificities of clinical, parasitological and serological tests for detection of canine infection by Leishmania chagasi were estimated using latent class analysis, considering four types of models and different cutoffs. The best sensitivity estimates for the clinical, serological and parasitological tests were 60%, 95% and 66% respectively. The best estimates for the specificity of clinical, serological and parasitological tests were 77%, 90% and 100% respectively. It is concluded that the use of parasitological assays as the gold standard for validation of diagnostic tests is not appropriate and that the indicators of accuracy of the tests evaluated are insufficient to justify that they are used alone for diagnosis of infection in order to control the disease.

Orientador: Luiz Henrique Antunes Rodrigues / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-11T10:02:19Z (GMT). No. of bitstreams: 1 Meira_CarlosAlbertoAlves_D.pdf: 2588338 bytes, checksum: 869cc28d2c71dbc901870285cc32d8f9 (MD5) Previous issue date: 2008 / Resumo: Sistemas de alerta de doenças de plantas permitem racionalizar o uso de agrotóxicos, mas são pouco utilizados na prática. Complexidade dos modelos, dificuldade de obtenção dos dados necessários e custos para o agricultor estão entre as razões que inibem o seu uso. Entretanto, o desenvolvimento tecnológico recente - estações meteoro lógicas automáticas, bancos de dados, monitoramento agrometeorológico na Web e técnicas avançadas de análise de dados - permite se pensar em um sistema de acesso simples e gratuito. Uma instância do processo de descoberta de conhecimento em bases de dados foi realizada com o objetivo de avaliar o uso de classificação e de indução de árvores de decisão na análise e no alerta da ferrugem do cafeeiro causada por Hemileia vastatrix. Taxas de infecção calculadas a partir de avaliações mensais de incidência da ferrugem foram agrupadas em três classes: TXl - redução ou estagnação; TX2 - crescimento moderado (até 5 p.p.); e TX3 - crescimento acelerado (acima de 5 p.p.). Dados meteorológicos, carga pendente de frutos do cafeeiro (Coffea arabica) e espaçamento entre plantas foram as variáveis independentes. O conjunto de treinamento totalizou 364 exemplos, preparados a partir de dados coletados em lavouras de café em produção, de outubro de 1998 a outubro de 2006. Uma árvore de decisão foi desenvolvida para analisar a epidemia da ferrugem do cafeeiro. Ela demonstrou seu potencial como modelo simbólico e interpretável, permitindo a identificação das fronteiras de decisão e da lógica contidas nos dados, allf'iliando na compreensão de quais variáveis e como as interações dessas variáveis condicionaram o progresso da doença no campo. As variáveis explicativas mais importantes foram a temperatura média nos períodos de molhamento foliar, a carga pendente de frutos, a média das temperaturas máximas diárias no período de inG:!Jbação e a umidade relativa do ar. Os modelos de alerta foram deserivolvtdos considerando taxas de infecção binárias, segundo os limites de 5 p.p e 10 p.p. (classe- '1' para taxas maiores ou iguais ao limite; classe 'O', caso contrário). Os modelos são específicos para lavouras com alta carga pendente ou para lavouras com baixa carga. Os primeiros tiveram melhor desempenho na avaliação. A estimativa de acurácia, por validação cruzada, foi de até 83%, considerando o alerta a partir de 5 p.p. Houve ainda equilíbrio entre a acurácia e medidas importantes como sensitividade, especificidade e confiabilidade positiva ou negativa. Considerando o alerta a partir de 10 p.p., a acurácia foi de 79%. Para lavouras com baixa carga pendente, os modelos considerando o alerta a partir de 5 p.p. tiveram acurácia de até 72%. Os modelos para a taxa de infecção mais elevada (a partir de 10 p.p.) tiveram desempenho fraco. Os modelos mais bem avaliados mostraram ter potencial para servir como apoio na tomada de decisão referente à adoção de medidas de controle da ferrugem do cafeeiro. O processo de descoberta de conhecimento em bases de dados foi caracterizado, com a intenção de que possa vir a ser útil em aplicações semelhantes para outras culturas agrícolas ou para a própria cultura do café, no caso de outras doenças ou pragas / Abstract: Plant disease warning systems can contribute for diminishing the use of chemicals in agriculture, but they have received limited acceptance in practice. Complexity of models, difficulties in obtaining the required data and costs for the growers are among the reasons that inhibit their use. However, recent technological advance - automatic weather stations, databases, Web based agrometeorological monitoring and advanced techniques of data analysis - allows the development of a system with simple and free access. A process .instance of knowledge discovery in databases has been realized to evaluate the use of classification and decision tree induction in the analysis and warning of coffee rust caused by Hemileia vastatrix. Infection rates calculated from monthly assessments of rust incidence were grouped into three classes: TXl - reduction or stagnation; TX2 - moderate growth (up to 5 pp); and TX3 - accelerated growth (above 5 pp). Meteorological data, expected yield and space between plants were used as independent variables. The training data set contained 364 examples prepared from data collected in coffee-growing areas between October 1998 and October 2006. A decision tree has been developed to analyse the coffee rust epidemics. The decision tree demonstrated its potential as a symbolic and interpretable model. Its mo deI representation identified the existing decision boundaries in the data and the logic underlying them, helping to understand which variables, and interactions between these variables, led to, coffee rust epidemics in the field. The most important explanatory variables were mean temperature during leaf wetness periods, expected yield, mean of maximum temperatures during the incubation period and relative air humidity. The warning models have been developed considering binary infection rates, according to the 5 pp and 10 pp thresholds, (class '1' for rates greater than or equal the threshold; class 'O;, otherwise). These models are specific for growing are as with high expected yield or areas with low expected yield. The former had best performance in the evaluation. The estimated accuracy by cross-validation was up to 83%, considering the waming for 5 pp and higher. There was yet equivalence between accuracy and such important measures like sensitivity, specificity a~d positive or negative reliability. Considering the waming for 10 pp and higher, the accuracy was 79%. For growing areas with low expected yield, the accuracy of the models considering the waming for 5 pp and higher was up to 72%. The models for the higher infection rate (10 pp and higher) had low performance. The best evaluated models showed potential to be used in decision making about coffee rust disease control. The process of knowledge discovery in databases was characterized in such a way it can be employed in similar problems of the application domain with other crops or other coffee diseases or pests / Doutorado / Planejamento e Desenvolvimento Rural Sustentável / Doutor em Engenharia Agrícola