917 resultados para Spatial data warehouse
Resumo:
Recent findings suggest that the visuo-spatial sketchpad (VSSP) may be divided into two sub-components processing dynamic or static visual information. This model may be useful to elucidate the confusion of data concerning the functioning of the VSSP in schizophrenia. The present study examined patients with schizophrenia and matched controls in a new working memory paradigm involving dynamic (the Ball Flight Task - BFT) or static (the Static Pattern Task - SPT) visual stimuli. In the BFT, the responses of the patients were apparently based on the retention of the last set of segments of the perceived trajectory, whereas control subjects relied on a more global strategy. We assume that the patients' performances are the result of a reduced capacity in chunking visual information since they relied mainly on the retention of the last set of segments. This assumption is confirmed by the poor performance of the patients in the static task (SPT), which requires a combination of stimulus components into object representations. We assume that the static/dynamic distinction may help us to understand the VSSP deficits in schizophrenia. This distinction also raises questions about the hypothesis that visuo-spatial working memory can simply be dissociated into visual and spatial sub-components.
Resumo:
The Technologies setting at Agricultural production system have the main characteristics the vertical productivity, reduced costs, soil physical, chemical and biological improvement to promote production sustainable growth. Thus, the study aimed to determine the variability and the linear and special correlations between the plant and soil attributes in order to select and indicate good representation of soil physical quality for forage productivity. In the growing season of 2006, on the Fazenda Bonança in Pereira Barreto (SP), the productivity of autumn corn forage (FDM) in an irrigated no-tillage system and the soil physical properties were analyzed. The purpose was to study the variability and the linear and spatial correlations between the plant and soil properties, to select an indicator of soil physical quality related to corn forage yield. A geostatistical grid was installed to collect soil and plant data, with 125 sampling points in an area of 2,500 m². The results show that the studied properties did not vary randomly and that data variability was low to very high, with well-defined spatial patterns, ranging from 7.8 to 38.0 m. On the other hand, the linear correlation between the plant and the soil properties was low and highly significant. The pairs forage dry matter versus microporosity and stem diameter versus bulk density were best correlated in the 0-0.10 m layer, while the other pairs - forage dry matter versus macro - and total porosity - were inversely correlated in the same layer. However, from the spatial point of view, there was a high inverse correlation between forage dry matter with microporosity, so that microporosity in the 0-0.10 m layer can be considered a good indicator of soil physical quality, with a view to corn forage yield.
Resumo:
Under field conditions, thermal diffusivity can be estimated from soil temperature data but also from the properties of soil components together with their spatial organization. We aimed to determine soil thermal diffusivity from half-hourly temperature measurements in a Rhodic Kanhapludalf, using three calculation procedures (the amplitude ratio, phase lag and Seemann procedures), as well as from soil component properties, for a comparison of procedures and methods. To determine thermal conductivity for short wave periods (one day), the phase lag method was more reliable than the amplitude ratio or the Seemann method, especially in deeper layers, where temperature variations are small. The phase lag method resulted in coherent values of thermal diffusivity. The method using properties of single soil components with the values of thermal conductivity for sandstone and kaolinite resulted in thermal diffusivity values of the same order. In the observed water content range (0.26-0.34 m³ m-3), the average thermal diffusivity was 0.034 m² d-1 in the top layer (0.05-0.15 m) and 0.027 m² d-1 in the subsurface layer (0.15-0.30 m).
Resumo:
A good knowledge of the spatial distribution of clay minerals in the landscape facilitates the understanding of the influence of relief on the content and crystallographic attributes of soil minerals such as goethite, hematite, kaolinite and gibbsite. This study aimed at describing the relationships between the mineral properties of the clay fraction and landscape shapes by determining the mineral properties of goethite, hematite, kaolinite and gibbsite, and assessing their dependence and spatial variability, in two slope curvatures. To this end, two 100 × 100 m grids were used to establish a total of 121 regularly spaced georeferenced sampling nodes 10 m apart. Samples were collected from the layer 0.0-0.2 m and analysed for iron oxides, and kaolinite and gibbsite in the clay fraction. Minerals in the clay fraction were characterized from their X-ray diffraction (XRD) patterns, which were interpreted and used to calculate the width at half height (WHH) and mean crystallite dimension (MCD) of iron oxides, kaolinite, and gibbsite, as well as aluminium substitution and specific surface area (SSA) in hematite and goethite. Additional calculations included the goethite and hematite contents, and the goethite/(goethite+hematite) [Gt/(Gt+Hm)] and kaolinite/(kaolinite+gibbsite) [Kt/(Kt+Gb)] ratios. Mineral properties were established by statistical analysis of the XRD data, and spatial dependence was assessed geostatistically. Mineralogical properties differed significantly between the convex area and concave area. The geostatistical analysis showed a greater number of mineralogical properties with spatial dependence and a higher range in the convex than in the concave area.
Resumo:
Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.
Resumo:
THESIS ABSTRACTThis thesis project was aimed at studying the molecular mechanisms underlying learning and memory formation, in particular as they relate to the metabolic coupling between astrocytes and neurons. For that, changes in the metabolic activity of different mice brain regions after 1 or 9 days of training in an eight-arm radial maze were assessed by (14C) 2-deoxyglucose (2DG) autoradiography. Significant differences in the areas engaged during the behavioral task at day 1 (when animals are confronted for the first time to the learning task) and at day 9 (when animals are highly performing) have been identified. These areas include the hippocampus, the fornix, the parietal cortex, the laterodorsal thalamic nucleus and the mammillary bodies at day 1 ; and the anterior cingulate, the retrosplenial cortex and the dorsal striatum at day 9. Two of these cerebral regions (those presenting the greatest changes at day 1 and day 9: the hippocampus and the retrosplenial cortex, respectively) were microdissected by laser capture microscopy and selected genes related to neuron-glia metabolic coupling, glucose metabolism and synaptic plasticity were analyzed by RT-PCR. 2DG and gene expression analysis were performed at three different times: 1) immediately after the end of the behavioral paradigm, 2) 45 minutes and 3) 6 hours after training. The main goal of this study was the identification of the metabolic adaptations following the learning task. Gene expression results demonstrate that the learning task profoundly modulates the pattern of gene expression in time, meaning that these two cerebral regions with high 2DG signal (hippocampus and retrosplenial cortex) have adapted their metabolic molecular machinery in consequence. Almost all studied genes show a higher expression in the hippocampus at day 1 compared to day 9, while an increased expression was found in the retrosplenial cortex at day 9. We can observe these molecular adaptations with a short delay of 45 minutes after the end of the task. However, 6 hours after training a high gene expression was found at day 9 (compared to day 1) in both regions, suggesting that only one day of training is not sufficient to detect transcriptional modifications several hours after the task. Thus, gene expression data match 2DG results indicating a transfer of information in time (from day 1 to day 9) and in space (from the hippocampus to the retrosplenial cortex), and this at a cellular and a molecular level. Moreover, learning seems to modify the neuron-glia metabolic coupling, since several genes involved in this coupling are induced. These results also suggest a role of glia in neuronal plasticity.RESUME DU TRAVAIL DE THESECe projet de thèse a eu pour but l'étude des mécanismes moléculaires qui sont impliqués dans l'apprentissage et la mémoire et, en particulier, à les mettre en rapport avec le couplage métabolique existant entre les astrocytes et les neurones. Pour cela, des changements de l'activité métabolique dans différentes régions du cerveau des souris après 1 ou 9 jours d'entraînement dans un labyrinthe radial à huit-bras ont été évalués par autoradiographie au 2-désoxyglucose (2DG). Des différences significatives dans les régions engagées pendant la tâche comportementale au jour 1 (quand les animaux sont confrontés pour la première fois à la tâche) et au jour 9 (quand les animaux ont déjà appris) ont été identifiés. Ces régions incluent, au jour 1, l'hippocampe, le fornix, le cortex pariétal, le noyau thalamic laterodorsal et les corps mamillaires; et, au jour 9, le cingulaire antérieur, le cortex retrosplenial et le striatum dorsal. Deux de ces régions cérébrales (celles présentant les plus grands changements à jour 1 et à jour 9: l'hippocampe et le cortex retrosplenial, respectivement) ont été découpées par microdissection au laser et quelques gènes liés au couplage métabolique neurone-glie, au métabolisme du glucose et à la plasticité synaptique ont été analysées par RT-PCR. L'étude 2DG et l'analyse de l'expression de gènes ont été exécutés à trois temps différents: 1) juste après entraînement, 2) 45 minutes et 3) 6 heures après la fin de la tâche. L'objectif principal de cette étude était l'identification des adaptations métaboliques suivant la tâche d'apprentissage. Les résultats de l'expression de gènes démontrent que la tâche d'apprentissage module profondément le profile d'expression des gènes dans le temps, signifiant que ces deux régions cérébrales avec un signal 2DG élevé (l'hippocampe et le cortex retrosplenial) ont adapté leurs « machines moléculaires » en conséquence. Presque tous les gènes étudiés montrent une expression plus élevée dans l'hippocampe au jour 1 comparé au jour 9, alors qu'une expression accrue a été trouvée dans le cortex retrosplenial au jour 9. Nous pouvons observer ces adaptations moléculaires avec un retard court de 45 minutes après la fin de la tâche. Cependant, 6 heures après l'entraînement, une expression de gènes élevée a été trouvée au jour 9 (comparé à jour 1) dans les deux régions, suggérant que seulement un jour d'entraînement ne suffit pas pour détecter des modifications transcriptionelles plusieurs heures après la tâche. Ainsi, les données d'expression de gènes corroborent les résultats 2DG indiquant un transfert d'information dans le temps (de jour 1 à jour 9) et dans l'espace (de l'hippocampe au cortex retrosplenial), et ceci à un niveau cellulaire et moléculaire. D'ailleurs, la tâche d'apprentissage semble modifier le couplage métabolique neurone-glie, puisque de nombreux gènes impliqués dans ce couplage sont induits. Ces observations suggèrent un rôle important de la glie dans les mécanismes de plasticité du système nerveux.
Resumo:
The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.
Resumo:
Information underlying analyses of coffee fertilization systems should consider both the soil and the nutritional status of plants. This study investigated the spatial relationship between phosphorus (P) levels in coffee plant tissues and soil chemical and physical properties. The study was performed using two arabica and one canephora coffee variety. Sampling grids were established in the areas, and the points georeferenced. The assessed properties of the soil were levels of available phosphorus (P-Mehlich), remaining phosphorus (P-rem) and particle size, and of the plant tissue, phosphorus levels (foliar P). The data were subjected to descriptive statistical analysis, correlation analysis, cluster analysis, and probability tests. Geostatistical and trend analyses were only performed for pairs of variables with significant linear correlation. The spatial variability for foliar P content was high for the variety Catuai and medium for the other evaluated plants. Unlike P-Mehlich, the variability in P-rem of the soil indicated the nutritional status of this nutrient in the plant.
Resumo:
The assessment of spatial uncertainty in the prediction of nutrient losses by erosion associated with landscape models is an important tool for soil conservation planning. The purpose of this study was to evaluate the spatial and local uncertainty in predicting depletion rates of soil nutrients (P, K, Ca, and Mg) by soil erosion from green and burnt sugarcane harvesting scenarios, using sequential Gaussian simulation (SGS). A regular grid with equidistant intervals of 50 m (626 points) was established in the 200-ha study area, in Tabapuã, São Paulo, Brazil. The rate of soil depletion (SD) was calculated from the relation between the nutrient concentration in the sediments and the chemical properties in the original soil for all grid points. The data were subjected to descriptive statistical and geostatistical analysis. The mean SD rate for all nutrients was higher in the slash-and-burn than the green cane harvest scenario (Student’s t-test, p<0.05). In both scenarios, nutrient loss followed the order: Ca>Mg>K>P. The SD rate was highest in areas with greater slope. Lower uncertainties were associated to the areas with higher SD and steeper slopes. Spatial uncertainties were highest for areas of transition between concave and convex landforms.
Resumo:
Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.
Resumo:
Summary The present thesis work focused on the ecology of benthic invertebrates in the proglacial floodplain of the Rhone in the Swiss Alps. The main glacial Rhone River and a smaller glacial tributary, the Mutt River, joined and entered a braiding multi-thread area. A first part concentrated on the disruption of the longitudinal patterns of environmental conditions and benthic invertebrate fauna in the Rhone by its tributary the Mutt. The Mutt had less harsh environmental conditions, higher taxonomic richness and more abundant zoobenthos compared to the Rhone upstream of the confluence. Although the habitat conditions in the main stream were little modified by the tributary, the fauna was richer and more diverse below the confluence. Colonisation from the Mutt induced the occurrence of faunal elements uncommon of glacial streams in the upper Rhone, where water temperature remains below 4°C. Although the glacial Rhone dominated the system with regard to hydrology and certain environmental conditions, the Mutt tributary has to be seen as the faunal driver of the system. The second part of the study concerned the spatio-temporal differentiation of the habitats and the benthic communities along and across the flood plain. No longitudinal differentiation was found. The spatial transversal differentiation of three habitat types with different environmental characteristics was successfully reflected in the spatial variability of benthic assemblages. This typology separated marginal sites of the flood plain, left bank sites under the influence of the Mutt, and the right bank sites under the influence of the Rh6ne. Faunistic spatial differences were emphasized by the quantitative structure of the fauna, richness, abundances and Simpson index of diversity. Seasonal environmental variability was positively related with Simpson index of diversity and the total richness per site. Low flow conditions were the most favourable season for the fauna and November was characterized by low spatial environmental heterogeneity, high spatial heterogeneity of faunal assemblage, maximum taxonomic richness, a particular taxonomic composition, highest abundances, as well as the highest primary food resources. The third part studied the egg development of three species of Ephemeroptera in the laboratory at 1.5 to 7°C and the ecological implications in the field. Species revealed very contrasting development strategies. Baetis alpinus has a synchronous and efficient egg development, which is faster in warmer habitats, enabling it to exploit short periods of favourable conditions in the floodplain. Ecdyonurus picteti has a very long development time slightly decreasing in warmer conditions. The high degree of individual variation suggests a genetic determination of the degree-days demand. Combined with the glacial local conditions, this strategy leads to an extreme delay of hatching and allows it to develop in very unpredictable habitats. Rhithrogena nivata is the second cold adapted species in Ephemeroptera. The incubation duration is long and success largely depends on the timing of hatching and the discharge conditions. This species is able to exploit extremely unstable and cold habitats where other species are limited by low water temperatures. The fourth part dealt with larval development in different habitats of the floodplain. Addition of data on egg development allowed the description of the life histories of the species from oviposition until emergence. Rhithrogena nivata and loyolaea generally have a two-year development, with the first winter passed as eggs and the second one as larvae. Development of Ecdyonurus picteti is difficult to document but appears to be efficient in a harsh and unpredictable environment. Baetis alpinus was studied separately in four habitats of the floodplain system with contrasting thermal regimes. Differences in success and duration of larval development and in growth rates are emphasised. Subvention mechanisms between habitats by migration of young or grown larvae were demonstrated. Development success and persistence of the populations in the system were thus increased. Emergence was synchronised to the detriment of the optimisation of the adult's size and fecundity. These very different development strategies induce a spatial and temporal distribution in the use of food resources and ecological niches. The last part of this work aimed at the synthesis of the characteristics and the ecological features of three distinct compartments of the system that are the upper Rhone, the Mutt and the floodplain. Their particular role as well as their inter-dependence concerning the structure and the dynamics of the benthic communities was emphasised. Résumé Ce travail de thèse est consacré à l'écologie des invertébrés benthiques dans la zone alluviale proglaciaire du Rhône dans les Alpes suisses. Le Rhône, torrent glaciaire principal, reçoit les eaux de la Mutt, affluent glaciaire secondaire, puis pénètre dans une zone de tressage formée de plusieurs bras. La première partie de l'étude se concentre sur la disruption par la Mutt des processus longitudinaux, tant environnementaux que faunistiques, existants dans le Rhône. Les conditions environnementales régnant dans la Mutt sont moins rudes, la richesse taxonomique plus élevée et le zoobenthos plus abondant que dans le Rhône en amont de la confluence. Bien que les conditions environnementales dans le torrent principal soient peu modifiées par l'affluent, la faune s'avère être plus riche et plus diversifiée en aval de la confluence. La colonisation depuis la Mutt permet l'occurrence de taxons inhabituels dans le Rhône en amont de la confluence, où la température de l'eau se maintient en dessous de 4°C. Bien que le Rhône, torrent glaciaire principal, domine le système du point de vu de l'hydrologie et de certains paramètres environnementaux, l'affluent Mutt doit être considéré comme l'élément structurant la faune dans le système. La deuxième partie concerne la différentiation spatiale et temporelle des habitats et des communautés benthiques à travers la plaine alluviale. Aucune différentiation longitudinale n'a été mise en évidence. La différentiation transversale de trois types d'habitats sur la base des caractéristiques environnementales a été confirmée par la variabilité spatiale de la faune. Cette typologie sépare les sites marginaux de la plaine alluviale, ceux sous l'influence de la Mutt (en rive gauche) et ceux sous l'influence du Rhône amont (en rive droite). Les différences spatiales de la faune sont mises en évidence par la structure quantitative de la faune, la richesse, les abondances et l'indice de diversité de Simpson. La variabilité saisonnière du milieu est positivement liée avec l'indice de diversité de Simpson et la richesse totale par site. L'étiage correspond à la période la plus favorable pour la faune et novembre réunit des conditions de faible hétérogénéité spatiale du milieu, de forte hétérogénéité spatiale de la faune, une richesse taxonomique maximale, une composition faunistique particulière, les abondances ainsi que les ressources primaires les plus élevées. La troisième partie est consacrée à l'étude du développement des oeufs de trois espèces d'Ephémères au laboratoire à des températures de 1.5 à 7°C, ainsi qu'aux implications écologiques sur le terrain. Ces espèces présentent des stratégies de développement très contrastées. Baetis alpinus a un développement synchrone et efficace, plus rapide en milieu plus chaud et lui permettant d'exploiter les courtes périodes de conditions favorables. Ecdyonurus picteti présente une durée de développement très longue, diminuant légèrement dans des conditions plus chaudes. L'importante variation interindividuelle suggère un déterminisme génétique de la durée de développement. Cette stratégie, associée aux conditions locales, conduit à un décalage extrême des éclosions et permet à l'espèce de se développer dans des habitats imprévisibles. Rhithrogena nivata est la seconde espèce d'Ephémères présentant une adaptation au froid. L'incubation des oeufs est longue et son succès dépend de la période des éclosions et des conditions hydrologiques. Cette espèce est capable d'exploiter des habitats extrêmement instables et froids, où la température est facteur limitant pour d'autres espèces. La quatrième partie traite du développement larvaire dans différents habitats de la plaine alluviale. Le développement complet est décrit pour les espèces étudiées de la ponte jusqu'à l'émergence. Rhithrogena nivata et loyolaea atteignent généralement le stade adulte en deux ans, le premier hiver étant passé sous forme d'oeuf et le second sous forme de larve. Le développement de Ecdyonurus picteti est difficile à documenter, mais s'avère cependant efficace dans un environnement rude et imprévisible. Baetis alpinus a été étudié séparément dans quatre habitats de la plaine ayant des régimes thermiques contrastés. La réussite et la durée du développement embryonnaire ainsi que les taux de croissance y sont variables. Des mécanismes de subvention entre habitats sont possibles par la migration de larves juvéniles ou plus développées, augmentant ainsi la réussite du développement et le maintien des populations dans le système. L'émergence devient synchrone, au détriment de l'optimisation de la taille et de la fécondité des adultes. Ces stratégies très différentes induisent une distribution spatiale et temporelle dans l'usage des ressources et des niches écologiques. La dernière partie synthétise les caractéristiques écologiques des trois compartiments du système que sont le Rhône amont, la Mutt et la zone alluviale. Leurs rôles particuliers et leurs interdépendances du point de vue de la structure et de la dynamique des communautés benthiques sont mis en avant.
Resumo:
The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.
Resumo:
In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.
Resumo:
Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.