992 resultados para Map Comparison


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Clinically childhood occipital lobe epilepsy (OLE) manifests itself with distinct syndromes. The traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the occipital lobes. To understand these syndromes it is important to map with more precision the epileptogenic cortical regions in OLE. Experimentally, we studied three idiopathic childhood OLE patients with EEG source analysis and with the simultaneous acquisition of EEG and fMRI, to map the BOLD effect associated with EEG spikes. The spatial overlap between the EEG and BOLD results was not very good, but the fMRI suggested localizations more consistent with the ictal clinical manifestations of each type of epileptic syndrome. Since our first results show that by associating the BOLD effect with interictal spikes the epileptogenic areas are mapped to localizations different from those calculated from EEG sources and that by using different EEG/fMRI processing methods our results differ to some extent, it is very important to compare the different methods of processing the localization of activation and develop a good methodology for obtaining co-registration maps of high resolution EEG with BOLD localizations.

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RESUMO: O uso de ratinhos transgénicos em neurociências aumentou consideravelmente nos últimos anos devido ao crescente interesse em compreender o cérebro e a necessidade de solucionar situações clínicas do foro neurológico e psiquiátrico. Para esse efeito, diferentes métodos de produção de animais transgénicos têm sido testados. O objectivo desta tese foi comparar métodos de integração aleatória de um transgene no genoma de ratinhos em termos de eficiência, estabilidade da integração do transgene, número de animais e de horas de trabalho necessárias para cada método. Assim, foi comparado o método mais utilizado - microinjecção pronuclear (PNMI) - com duas outras técnicas cujo desempenho foi considerado promissor – a transferência génica através dos testículos por electroporação e transfecção por lentivírus in vivo. As três técnicas foram realizadas usando um gene repórter sob o controlo de um promotor constitutivo, e depois reproduzidas usando um gene de interesse de modo a permitir obtenção de um animal capaz de ser usado em experimentação laboratorial. O transgene de interesse utilizado codifica uma proteína de fusão correspondendo a uma variante da rodopsina (channelrhodopsin) fundida à proteína enhanced yellow fluorescente protein ((EYFP) resultando num produto designado ChR2-EYFP. Este animal transgénico apresentaria expressão deste canal iónico apenas em células dopaminergicas, o que, com manipulação optogenética, tornaria possivel a activação especifica deste grupo de neurónios e, simultaneamente, a observação do impacto desta manipulação no comportamento num animal em livre movimento. Estas ferramentas são importantes na investigação básica em neurociências pois ajudam a esclarecer o papel de grupos específicos de neurónios e compreender doenças como a doença de Parkinson ou a esquizofrenia onde a função de certos tipos de neurónios de encontra alterada. Quando comparados os três métodos realizados verifica-se que usando um gene repórter PMNI resulta em 31,3% de, a de animais transgénicos obtidos, a electroporação de testículos em 0% e a injecção de lentivírus em 0%. Quando usado o gene de interesse, os resultados obtidos são, respectivamente, 18,8%, 63,9% e 0%.--------------ABSTRACT: The use of transgenic mice is increasing in all fields of research, particularly in neuroscience, due to the widespread need of animal models to solve neurological and psychiatric medical conditions. Different methodologies have been tested in the last decades in order to produce such transgenic animals. The ultimate goal of this thesis is to compare different methods of random integration of a transgene in the genome of mice in terms of efficiency, stability of the transgene integration, number of animals required and the labour intensity of each technique. We compared the most used method – pronuclear microinjection (PNMI) – with two other promising techniques – Testis Mediated Gene Transfer (TMGT) by electroporation and in vivo lentiviral transfection. The three techniques were performed using a reporter gene – green fluorescent protein (GFP), whose transcription was driven by the constitutive cytomegalovirus (CMV) promoter. These three techniques were later reproduced using the tyrosine hydroxylase promoter (TH) and the neuronal manipulator, channelrhodopsin-2 fused to the enhanced yellow fluorescent reporter protein (ChR2-EYFP). The transgenic animal we sough to produce would express the light driven channel only in dopaminergic cells, making possible to specifically activate this group of neurons, while simultaneously observe the behaviour in a freely moving animal. This is a very important tool in basic neuroscience research since it helps to clarify the role of specific groups of neurons, map circuits in the brain, and consequently understand neurological diseases such as Parkinson’s disease or schizophrenia, where the function of certain types of neurons is affected. When comparing the three methods, it was verified that using a reporter gene PNMI resulted in 31.3% of transgenic mice obtained, testis electroporation in 0% and lentiviral injection in 0%. When using the gene of interest, the results obtained were, respectively, 18.8%, 63.9% and 0%.

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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.

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Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

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Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120-190 and 250-300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250-300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

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Purpose: To evaluate the reproducibility of Cirrus-SD OCT measurements and to compare central macular thickness (CMT) measurements between TD-Stratus and SD-Cirrus OCT in patients with active exudative AMD. Methods: Consecutive case series of patients with active exudative AMD seen in the Medical Retina Department. Patients underwent 1 scan with Stratus (macular thickness map protocol) and 5 scans with Cirrus (Macular Cube protocol) at the same visit by the same experienced examiner. To be included, patients best-corrected visual acuity (BCVA) had to be >20/200 while all scans had to be of sufficient quality, well-centered and at least one Cirrus scan with CMT >300 microns. The repeatability of the SD Cirrus was estimated by using all 5 CMT measurements and the mean of the Cirrus measurements was compared with the CMT obtained by TD Stratus. Results: Cirrus OCT demonstrated high intraobserver repeatability at the central foveal region (ICC 96%). The mean of the CMT measurements was 321microns for Stratus and 387 microns for Cirrus. The average difference was 65m (SD=30). The coefficient of concordance between Stratus and Cirrus CMT measurements was rho=0,749 with a high precision and a moderate accuracy. The equation of the line of regression between Stratus and meanCirrus is given by the following: M_stratus = 0,848 x m_cirrus - 4,496 (1).Conclusions: The Cirrus macular cube protocol allows reproducible CMT measurements in patients with active exudative AMD. In cases of upgrading from TD to SD use and vice versa, there is the possibility to predict the measurements by using the equation (1). These real life data and conclusions can help in improving our clinical management of patients with neovascular AMD.

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El objetivo de la presente investigación fue analizar la correspondencia entre los resultados de una evaluación de tierras con la distribución real de los cultivos. Para ello la aptitud biofísica de las tierras se comparó con diferentes tipologías de frecuencia de ocurrencia de los cultivos y rotaciones derivadas de mapas de cultivos multitemporales. La investigación fue llevada a cabo en el distrito de riego de Flumen (33.000 ha), localizado en el valle del Ebro (NE España). La evaluación de tierras se basó en una cartografía de suelos 1:100.000, según el esquema FAO, para los principales cultivos presentes en el área de estudio (alfalfa, cereales de invierno, maíz, arroz y girasol). Se utilizaron tres mapas de frecuencia de cultivos y un mapa de rotaciones, derivado de una serie temporal de imágenes Landsat TM y ETM+ del periodo 1993-2000, y se compararon con los mapas de aptitud de tierras para los diferentes cultivos. Se analizó estadísticamente (Pearson χ2, Cramer V, Gamma y Somers D) la relación entre los dos tipos de variables. Los resultados muestran la existencia de una relación significativa (P=0,001) entre la localización de los cultivos y la idoneidad de las tierras, excepto de cultivos oportunistas como el girasol, muy influenciado por las subvenciones en el periodo estudiado. Las rotaciones basadas en la alfalfa muestran los mayores porcentajes (52%) de ocupación en las tierras más aptas para la agricultura en el área de estudio. El presente enfoque multitemporal de análisis de la información ofrece una visión más real que la comparación entre un mapa de evaluación de tierras y un mapa de cultivos de una fecha determinada, cuando se valora el grado de acuerdo entre las recomendaciones sobre la aptitud de las tierras y los cultivos realmente cultivados por los agricultores.

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This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.

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A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

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Baroreflex sensitivity was studied in the same group of conscious rats using vasoactive drugs (phenylephrine and sodium nitroprusside) administered by three different approaches: 1) bolus injection, 2) steady-state (blood pressure (BP) changes produced in steps), 3) ramp infusion (30 s, brief infusion). The heart rate (HR) responses were evaluated by the mean index (mean ratio of all HR changes and mean arterial pressure (MAP) changes), by linear regression and by the logistic method (maximum gain of the sigmoid curve by a logistic function). The experiments were performed on three consecutive days. Basal MAP and resting HR were similar on all days of the study. Bradycardic responses evaluated by the mean index (-1.5 ± 0.2, -2.1 ± 0.2 and -1.6 ± 0.2 bpm/mmHg) and linear regression (-1.8 ± 0.3, -1.4 ± 0.3 and -1.7 ± 0.2 bpm/mmHg) were similar for all three approaches used to change blood pressure. The tachycardic responses to decreases of MAP were similar when evaluated by linear regression (-3.9 ± 0.8, -2.1 ± 0.7 and -3.8 ± 0.4 bpm/mmHg). However, the tachycardic mean index (-3.1 ± 0.4, -6.6 ± 1 and -3.6 ± 0.5 bpm/mmHg) was higher when assessed by the steady-state method. The average gain evaluated by logistic function (-3.5 ± 0.6, -7.6 ± 1.3 and -3.8 ± 0.4 bpm/mmHg) was similar to the reflex tachycardic values, but different from the bradycardic values. Since different ways to change BP may alter the afferent baroreceptor function, the MAP changes obtained during short periods of time (up to 30 s: bolus and ramp infusion) are more appropriate to prevent the acute resetting. Assessment of the baroreflex sensitivity by mean index and linear regression permits a separate analysis of gain for reflex bradycardia and reflex tachycardia. Although two values of baroreflex sensitivity cannot be evaluated by a single symmetric logistic function, this method has the advantage of better comparing the baroreflex sensitivity of animals with different basal blood pressures.

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Pumping, fan and compressor systems consume most of the motor electricity power in both the industrial and services sectors. A variable speed drive brings relevant improvements in a fluid system leading to energy saving that further on can be translated into Mtons reduction of CO 2 emissions. Standards and regulations are being adopted for fluid handling systems to limit the less efficiency pumps out of the European market on the coming years and a greater potential in energy savings is dictated by the Energy Efficiency Index (EEI) requirements for the whole pumping system and integrated pumps. Electric motors also have an International Efficiency (IE) classification in order to introduce higher efficiency motors into the market. In this thesis, the applicability of mid-size common electric motor types to industrial pumping system took place comparing the motor efficiency characteristics with each other and by analyzing the effect of motor dimensioning on the pumping system and its impact in the energy consumption.

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14C-dated pollen and lake-level data from Europe are used to assess the spatial patterns of climate change between 6000 yr BP and present, as simulated by the NCAR CCM1 (National Center for Atmospheric Research, Community Climate Model, version 1) in response to the change in the Earth’s orbital parameters during this perod. First, reconstructed 6000 yr BP values of bioclimate variables obtained from pollen and lake-level data with the constrained-analogue technique are compared with simulated values. Then a 6000 yr BP biome map obtained from pollen data with an objective biome reconstruction (biomization) technique is compared with BIOME model results derived from the same simulation. Data and simulations agree in some features: warmer-than-present growing seasons in N and C Europe allowed forests to extend further north and to higher elevations than today, and warmer winters in C and E Europe prevented boreal conifers from spreading west. More generally, however, the agreement is poor. Predominantly deciduous forest types in Fennoscandia imply warmer winters than the model allows. The model fails to simulate winters cold enough, or summers wet enough, to allow temperate deciduous forests their former extended distribution in S Europe, and it incorrectly simulates a much expanded area of steppe vegetation in SE Europe. Similar errors have also been noted in numerous 6000 yr BP simulations with prescribed modern sea surface temperatures. These errors are evidently not resolved by the inclusion of interactive sea-surface conditions in the CCM1. Accurate representation of mid-Holocene climates in Europe may require the inclusion of dynamical ocean–atmosphere and/or vegetation–atmosphere interactions that most palaeoclimate model simulations have so far disregarded.

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Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada, the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover.