Contract-program evaluation: Impact of the DRG classification system on hospitals' outputs

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Retrospective histopathological classification of 1,108 skin biopsies from patients clinically suspected of having leprosy from Bahia, Northeast Brazil

We report a retrospective histopathological classification carried out under laboratory conditions by the method of Ridley & Jopling of 1,108 skin biopsies from patients clinically suspected of having leprosy from Bahia, Northeast Brazil.

Comparative analysis of multicriteria decision making methods

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Landscape composition and climatic parameters significant in the spread of an invasive species (Pine wood Nematode)

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente

Exploratory analysis of OpenStreetMap for land use classification

In the last years, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information. This huge amount of data might be hiding a vast geographical richness and therefore research needs to be conducted to explore their potential and use it in the solution of real world problems. In this study we conduct an exploratory analysis of data from the OpenStreetMap initiative. Using the Corine Land Cover database as reference and continental Portugal as the study area, we establish a possible correspondence between both classification nomenclatures, evaluate the quality of OpenStreetMap polygon features classification against Corine Land Cover classes from level 1 nomenclature, and analyze the spatial distribution of OpenStreetMap classes over continental Portugal. A global classification accuracy around 76% and interesting coverage areas’ values are remarkable and promising results that encourages us for future research on this topic.

Context classification for service robots

This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles.

Occurrence of Triatoma costalimai (Hemiptera: Reduviidae) in different environments and climatic seasons: a field study in the Brazilian savanna

INTRODUCTION: Trypanosoma cruzi-infected specimens of Triatoma costalimai have been detected in domiciliary units of Central Brazil, thereby maintaining the potential risk of vectorial transmission of Chagas disease. The aim of this study was to determine the occurrence and natural infection of T. costalimai in different environments (gallery forest, dry forest and peridomicile) and climatic seasons (wet and dry), in the municipality of Mambaí, State of Goiás, Brazil. METHODS: Triatomines were captured in October 2010 and in June 2011, employing two different methods (manual capture and mouse-baited adhesive traps). The insects were later separated by sex and nymphal stage, counted and examined parasitologically by abdominal compression and microscopic analysis of feces. RESULTS: Triatoma costalimai was found in three environments and in the two seasons studied. Overall, capture success of 900 traps and 60 blocks of rocks inspected was 5.8% and 11.7%, respectively. The occurrence of T. costalimai was higher among rocks in the peridomicile, where 97% of the 131 specimens were captured. The proportion of nymphs (98%) was much higher than that of adults, which were only detected in peridomicile. Most (95%) insects were captured during the wet season, with predominance of early-stage nymphs. None of the 43 specimens examined were infected by trypanosomatids. CONCLUSIONS: The results indicate a greater occurrence of T. costalimai in peridomiciliary environments and during the wet season in Mambaí, Goiás, highlighting the synanthropic behavior of this triatomine species in one area of the Brazilian savanna and the importance of entomological surveillance.

Using the International Classification of Functioning, Disability and Health as a tool for analysis of the effect of physical therapy on spasticity in HAM/TSP patients

INTRODUCTION: This study aimed to evaluate spasticity in human T-lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) patients before and after physical therapy using the International Classification of Functioning, Disability and Health (ICF). METHODS: Nine subjects underwent physical therapy. Spasticity was evaluated using the Modified Ashworth Scale. The obtained scores were converted into ICF body functions scores. RESULTS: The majority of subjects had a high degree of spasticity in the quadriceps muscles. According to the ICF codes, the spasticity decreased after 20 sessions of physical therapy. CONCLUSIONS: The ICF was effective in evaluating spasticity in HAM/TSP patients.

Susceptibility of Triatoma sordida Stal, 1859 (Hemiptera: Reduviidae) to alpha-cypermethrin under natural climatic conditions

Abstract:INTRODUCTION:Despite the recommendations by interpretation of resistance ratios obtained in laboratory bioassays, little is known about the actual impact of these results in the effectiveness of vector control activities in the field. In this context, our objective was to determine the mean value of different resistance ratios obtained by laboratory bioassays performed as part of the chemical control strategies of Triatoma sordida in the field.METHODS:Field bioassays were developed in Monte Azul and Coração de Jesus (Southeast, Brazil). In each location, samples were formed with three domestic units treated with alpha-cypermethrin 20.0% (Alfatek (r) 200 SC). One day after spraying, 10 fifth-instar nymphs remained in contact with the surfaces treated (adobe with plaster, adobe without plaster, or wood) with insecticide in plastic cones for 72h. Three cones were exposed inside the intradomicile and the peridomicile. The insects in the control group were exposed to an insecticide-free piece of cardboard. Mortality was measured 72h after removal of the insects from the treated surfaces. The tests were realized in triplicate.RESULTS:Mortality was 100.0% in all locations, except for Monte Azul; Landinho (96.6%) and Coração de Jesus; Barriguda (96.6%).CONCLUSIONS:Although the resistant populations in laboratory tests proved to be susceptible in the field, this observation is not sufficient to suggest that the cut-off points used to justify the resistance ratio should be changed. In this sense, we recommend that laboratory and field bioassays are carried out with a greater number of Triatominae populations to allow more in-depth consideration of the subject.

Evaluation of the World Health Organization 2009 classification of dengue severity in autopsied individuals, during the epidemics of 2011 and 2012 in Brazil

Abstract: INTRODUCTION: The dengue classification proposed by the World Health Organization (WHO) in 2009 is considered more sensitive than the classification proposed by the WHO in 1997. However, no study has assessed the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue. In the present study, we evaluated the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue in Northeast Brazil, where the disease is endemic. METHODS: This retrospective study included 121 autopsied individuals suspected of having dengue in Northeast Brazil during the epidemics of 2011 and 2012. All the autopsied individuals included in this study were confirmed to have dengue based on the findings of laboratory examinations. RESULTS: The median age of the autopsied individuals was 34 years (range, 1 month to 93 years), and 54.5% of the individuals were males. According to the WHO 1997 classification, 9.1% (11/121) of the cases were classified as dengue hemorrhagic fever (DHF) and 3.3% (4/121) as dengue shock syndrome. The remaining 87.6% (106/121) of the cases were classified as dengue with complications. According to the 2009 classification, 100% (121/121) of the cases were classified as severe dengue. The absence of plasma leakage (58.5%) and platelet counts <100,000/mm3 (47.2%) were the most frequent reasons for the inability to classify cases as DHF. CONCLUSIONS: The WHO 2009 classification is more sensitive than the WHO 1997 classification for identifying dengue deaths among autopsied individuals suspected of having dengue.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Climatic aspects of the Amazonian Tropical Forest

The purpose of this study is to analyse the climatic aspects of the data collected in a forest site in comparison with conventional data obtained at different sites, such as clearing, rural an urban areas. The results showed that diverse climatic conditions do exist among the sites: the urban site showed higher temperature and lower relative humidity. In addition, evapotranspiration (potential and actual rates) was computed from the forest data set, using the classical Penman-Monteith's equation. The actual evapotranspiration is 30% of the potential value during dry period and seems to be almost constant during the whole year (tipically 2.0 to 2.5 mm day-1).

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.