899 resultados para Multi-scale Fractal Dimension
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The integration of ecological principles into agricultural systems presents major opportunities for spreading risk at the crop and farm scale. This paper presents mechanisms by which diversity at several scales within the farming system can increase the stability of production. Diversity of above- and below-ground biota, but also genetic and phenotypic diversity within crops, has an essential role in safeguarding farm production. Novel mixtures of legume-grass leys have been shown to potentially provide significant benefits for pollinator and decomposer ecosystem services but to realise the greatest improvements carefully tailored farm management is needed such as mowing or grazing time, and the type and depth of cutivation. Complex farmland landscapes such as agroforestry systems have the potential to support pollinator abundance and diversity and spread risk across production enterprises. At the crop level, early results indicate that the vulnerability of pollen development, flowering and early grain set to abiotic stress can be ameliorated by managing flowering time through genotypic selection, and through the buffering effects of pollinators. Finally, the risk of sub-optimal quality in cereals can be mitigated through integration of near isogenic lines selected to escape specific abiotic stress events. We conclude that genotypic, phenotypic and community diversity can all be increased at multiple scales to enhance resilience in agricultural systems.
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Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.
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So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.
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Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.
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This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants. (C) 2008 Elsevier Inc. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fractal dimensions of grain boundary region in doped SnO2 ceramics were determined based on previously derived fractal model. This model considers fractal dimension as a measure of homogeneity of distribution of charge carriers. Application of the derived fractal model enables calculation of fractal dimension using results of impedance spectroscopy. The model was verified by experimentally determined temperature dependence of the fractal dimension of SnO2 ceramics. Obtained results confirm that the non-Debye response of the grain boundary region is connected with distribution of defects and consequently with a homogeneity of a distribution of the charge carriers. Also, it was found that C-T-1 function has maximum at temperature at which the change in dominant type of defects takes place. This effect could be considered as a third-order transition.
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Alkaline metal doped organic - inorganic hybrids have potential applications in the field of portable energy sources. Attractive sol - gel derived urea cross-linked polyether, siloxane - PPO ( poly( propylene oxide)) hybrids doped with sodium salts ( NaClO4 and NaBF4) were examined by multi-spectroscopic approach that includes complex impedance, X-ray powder diffraction (XRPD), small angle X-ray scattering (SAXS), Si-29 and Na-23 magic-angle spinning nuclear magnetic resonance (NMR/MAS), Na K-edge X-ray absorption near edge structure (XANES) and Raman spectroscopies. The goals of this work were to determine which cation coordinating site of the host matrix ( ether oxygen atoms or carbonyl oxygen atoms) is active in each of the materials analyzed, its influence on the nanostructure of the samples and its relation with the thermal and electrical properties. The main conclusion derived from this study is that the NaBF4 salt has a much lower solubility in the hybrid matrix than the NaClO4 salt. Furthermore, the addition of a large amount of salt plays a major role in the hybrid nanostructure and electrical properties, modifying the PPO chain conformation, weakening or breaking the hydrogen bond of the polyether - urea associations and changing the polycondensation and aggregation processes involving the siloxane species.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The estimation of the number of people in an area under surveillance is very important for the problem of crowd monitoring. When an area reaches an occupation level greater than the projected one, people's safety can be in danger. This paper describes a new technique for crowd density estimation based on Minkowski fractal dimension. Fractal dimension has been widely used to characterize data texture in a large number of physical and biological sciences. The results of our experiments show that fractal dimension can also be used to characterize levels of people congestion in images of crowds. The proposed technique is compared with a statistical and a spectral technique, in a test study of nearly 300 images of a specific area of the Liverpool Street Railway Station, London, UK. Results obtained in this test study are presented.
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The results of the histopathological analyses after the implantation of highly crystalline PVA microspheres in subcutaneous tissues of Wistar rats are here in reported. Three different groups of PVA microparticles were systematically studied: highly crystalline, amorphous, and commercial ones. In addition to these experiments, complementary analyses of architectural complexity were performed using fractal dimension (FD), and Shannon's entropy (SE) concepts. The highly crystalline microspheres induced inflammatory reactions similar to the ones observed for the commercial ones, while the inflammatory reactions caused by the amorphous ones were less intense. Statistical analyses of the subcutaneous tissues of Wistar rats implanted with the highly crystalline microspheres resulted in FD and SE values significantly higher than the statistical parameters observed for the amorphous ones. The FD and SE parameters obtained for the subcutaneous tissues of Wistar rats implanted with crystalline and commercial microparticles were statistically similar. Briefly, the results indicated that the new highly crystalline microspheres had biocompatible behavior comparable to the commercial ones. In addition, statistical tools such as FD and SE analyses when combined with histopathological analyses can be useful tools to investigate the architectural complexity tissues caused by complex inflammatory reactions. © 2012 WILEY PERIODICALS, INC.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.
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Aims: This study compared fractal dimension (FD) values on mandibular trabecular bone in digital and digitized images at different spatial and contrast resolutions. Materials and Methods: 12 radiographs of dried human mandibles were obtained using custom-fabricated hybrid image receptors composed of a periapical radiographic film and a photostimulable phosphor plate (PSP). The film/ PSP sets were disassembled, and the PSPs produced images with 600 dots per inch (dpi) and 16 bits. These images were exported as tagged image file format (TIFF), 16 and 8 bits, and 600, 300 and 150 dpi. The films were processed and digitized 3 times on a flatbed scanner, producing TIFF images with 600, 300 and 150 dpi, and 8 bits. On each image, a circular region of interest was selected on the trabecular alveolar bone, away from root apices and FD was calculated by tile counting method. Two-way ANOVA and Tukey’s test were conducted to compare the mean values of FD, according to image type and spatial resolution (α = 5%). Results: Spatial resolution was directly and inversely proportional to FD mean values and standard deviation, respectively. Spatial resolution of 150 dpi yielded significant lower mean values of FD than the resolutions of 600 and 300 dpi ( P < 0.05). A nonsignificant variability was observed for the image types ( P > 0.05). The interaction between type of image and level of spatial resolution was not signi fi cant (P > 0.05). Conclusion: Under the tested, conditions, FD values of the mandibular trabecular bone assessed either by digital or digitized images did not change. Furthermore, these values were in fluenced by lower spatial resolution but not by contrast resolution.