57 resultados para Spatial points patterns analysis

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The European Territorial Cohesion Policy has been the subject of numerous debates in recent years. Most contributions focus on understanding the term itself and figuring out what is behind it, or arguing for or against a stronger formal competence of the European Union in this field. This article will leave out these aspects and pay attention to (undefined and legally non-binding) conceptual elements of territorial cohesion, focusing on the challenge of linking it within spatial policies and organising the relations. Therefore, the theoretical approach of Cultural Theory and its concept of clumsy solution are applied to overcome the dilemma of typical dichotomies by adding a third and a fourth (but not a fifth) perspective. In doing so, normative contradictions between different rational approaches can be revealed, explained and approached with the concept of ‘clumsy solutions’. This contribution aims at discussing how this theoretical approach helps us explain and frame a coalition between the Territorial Cohesion Policy and spatial policies. This approach contributes to finding the best way of linking and organising policies, although the solution might be clumsy according to the different rationalities involved.

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Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

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This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

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Mayer H. Segmentation and segregation patterns of women-owned high-tech firms in four metropolitan regions in the United States, Regional Studies. The number of women starting and owning a business has increased dramatically and female entrepreneurs are entering non-traditional sectors such as high technology, construction and manufacturing. This paper investigates the trends in high-tech entrepreneurship by women in four US metropolitan regions (Silicon Valley, California; Boston, Massachusetts; Washington, DC; and Portland, Oregon). The research examines the sectoral and spatial segmentation patterns of women-owned high-tech firms. Although women are entering non-traditional sectors, the research finds that women entrepreneurs tend to own businesses in female-typed high-tech sectors. In established high-tech regions like Silicon Valley and Boston, male-typed and female-typed women-owned high-tech firms differ significantly in terms of sectoral and spatial segmentation regardless of firm age. While differences between male-typed and female-typed firms are not significant at the regional level for Washington, DC, the analysis shows significant intra-metropolitan differences for the female-typed high-tech firms. The paper concludes that sectoral and spatial segmentation are powerful dynamics that shape business ownership by women in high technology.

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This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

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Road traffic accidents (RTA) are an important cause of premature death. We examined socio-demographic and geographical determinants of RTA mortality in Switzerland by linking 2000 census data to RTA mortality records 2000-2005 (ICD-10 codes V00-V99). Data from 5.5 million residents aged 18-94 years, 1744 study areas, and 1620 RTA deaths were analyzed, including 978 deaths (60.4%) in motor vehicle occupants, 254 (15.7%) in motorcyclists, 107 (6.6%) in cyclists, and 259 (16.0%) in pedestrians. Weibull survival models and Bayesian methods were used to calculate hazard ratios (HR), and standardized mortality ratios (SMR) across study areas. Adjusted HR comparing women with men ranged from 0.04 (95% CI 0.02-0.07) in motorcyclists to 0.43 (95% CI 0.32-0.56) in pedestrians. There was a u-shaped relationship with age in motor vehicle occupants and motorcyclists. In cyclists and pedestrians, mortality increased after age 55 years. Mortality was higher in individuals with primary education (HR 1.53; 95% CI 1.29-1.81), and higher in single (HR 1.24; 95% CI 1.05-1.46), widowed (HR 1.31; 95% CI 1.05-1.65) and divorced individuals (HR 1.62; 95% CI 1.33-1.97), compared to persons with tertiary education or married persons. The association with education was particularly strong for pedestrians (HR 1.87; 95% CI 1.20-2.91). RTA mortality increased with decreasing population density of study areas for motor vehicle occupants (test for trend p<0.0001) and motorcyclists (p=0.0021) but not for cyclists (p=0.39) or pedestrians (p=0.29). SMR standardized for socio-demographic and geographical variables ranged from 82 to 190. Prevention efforts should aim to reduce inequities across socio-demographic and educational groups, and across geographical areas, with interventions targeted at high-risk groups and areas, and different traffic users, including pedestrians.

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Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

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Functional magnetic resonance imaging (fMRI) studies can provide insight into the neural correlates of hallucinations. Commonly, such studies require self-reports about the timing of the hallucination events. While many studies have found activity in higher-order sensory cortical areas, only a few have demonstrated activity of the primary auditory cortex during auditory verbal hallucinations. In this case, using self-reports as a model of brain activity may not be sensitive enough to capture all neurophysiological signals related to hallucinations. We used spatial independent component analysis (sICA) to extract the activity patterns associated with auditory verbal hallucinations in six schizophrenia patients. SICA decomposes the functional data set into a set of spatial maps without the use of any input function. The resulting activity patterns from auditory and sensorimotor components were further analyzed in a single-subject fashion using a visualization tool that allows for easy inspection of the variability of regional brain responses. We found bilateral auditory cortex activity, including Heschl's gyrus, during hallucinations of one patient, and unilateral auditory cortex activity in two more patients. The associated time courses showed a large variability in the shape, amplitude, and time of onset relative to the self-reports. However, the average of the time courses during hallucinations showed a clear association with this clinical phenomenon. We suggest that detection of this activity may be facilitated by examining hallucination epochs of sufficient length, in combination with a data-driven approach.

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Arabidopsis amino acid transporters (AAPs) show individual temporal and spatial expression patterns. A new amino acid transporter, AAP8 was isolated by reverse transcription-PCR. Growth and transport assays in comparison to AAP1-5 characterize AAP8 and AAP6 as high affinity amino acid transport systems from Arabidopsis. Histochemical promoter-beta-glucuronidase (GUS) studies identified AAP6 expression in xylem parenchyma, cells requiring high affinity transport due to the low amino acid concentration in xylem sap. AAP6 may thus function in uptake of amino acids from xylem. Histochemical analysis of AAP8 revealed stage-dependent expression in siliques and developing seeds. Thus AAP8 is probably responsible for import of organic nitrogen into developing seeds. The only missing transporter of the family AAP7 was nonfunctional in yeast with respect to amino acid transport, and expression was not detectable. Therefore, AAP6 and -8 are the only members of the family able to transport aspartate with physiologically relevant affinity. AAP1, -6 and -8 are the closest AAP paralogs. Although AAP1 and AAP8 originate from a duplicated region on chromosome I, biochemical properties and expression pattern diverged. Overlapping substrate specificities paired with individual properties and expression patterns point to specific functions of each of the AAP genes in nitrogen distribution rather than to mere redundancy.

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The European Mediterranean region is governed by a characteristic climate of summer drought that is likely to increase in duration and intensity under predicted climate change. However, large-scale network analyses investigating spatial aspects of pre-instrumental drought variability for this biogeographic zone are still scarce. In this study we introduce 54 mid- to high-elevation tree-ring width (TRW) chronologies comprising 2186 individual series from pine trees (Pinus spp.). This compilation spans a 4000-km east–west transect from Spain to Turkey, and was subjected to quality control and standardization prior to the development of site chronologies. A principal component analysis (PCA) was applied to identify spatial growth patterns during the network's common period 1862–1976, and new composite TRW chronologies were developed and investigated. The PCA reveals a common variance of 19.7% over the 54 Mediterranean pine chronologies. More interestingly, a dipole pattern in growth variability is found between the western (15% explained variance) and eastern (9.6%) sites, persisting back to 1330 AD. Pine growth on the Iberian Peninsula and Italy favours warm early growing seasons, but summer drought is most critical for ring width formation in the eastern Mediterranean region. Synoptic climate dynamics that have been in operation for the last seven centuries have been identified as the driving mechanism of a distinct east–west dipole in the growth variability of Mediterranean pines.

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Recent advances have revealed that during exogenous airway challenge, airway diameters can not be adequately predicted by their initial diameters. Furthermore, airway diameters can also vary greatly in time on scales shorter than a breath. In order to better understand these phenomena, we developed a multiscale model which allows us to simulate aerosol challenge in the airways during ventilation. The model incorporates agonist-receptor binding kinetics to govern the temporal response of airway smooth muscle (ASM) contraction on individual airway segments, which together with airway wall mechanics, determines local airway caliber. Global agonist transport and deposition is coupled with pressure-driven flow, linking local airway constrictions with global flow dynamics. During the course of challenge, airway constriction alters the flow pattern, redistributing agonist to less constricted regions. This results in a negative feedback which may be a protective property of the normal lung. As a consequence, repetitive challenge can cause spatial constriction patterns to evolve in time, resulting in a loss of predictability of airway diameters. Additionally, the model offers new insight into several phenomena including the intra- and inter-breath dynamics of airway constriction throughout the tree structure.

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In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

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The aim of this study was to investigate how oculomotor behaviour depends on the availability of colour information in pictorial stimuli. Forty study participants viewed complex images in colour or grey-scale, while their eye movements were recorded. We found two major effects of colour. First, although colour increases the complexity of an image, fixations on colour images were shorter than on their grey-scale versions. This suggests that colour enhances discriminability and thus affects low-level perceptual processing. Second, colour decreases the similarity of spatial fixation patterns between participants. The role of colour on visual attention seems to be more important than previously assumed, in theoretical as well as methodological terms.

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Temporal dynamics create unique and often ephemeral conditions that can influence soil microbial biogeography at different spatial scales. This study investigated the relation between decimeter to meter spatial variability of soil microbial community structure, plant diversity, and soil properties at six dates from April through November. We also explored the robustness of these interactions over time. An historically unfertilized, unplowed grassland in southwest Germany was selected to characterize how seasonal variability in the composition of plant communities and substrate quality changed the biogeography of soil microorganisms at the plot scale (10 m x 10 m). Microbial community spatial structure was positively correlated with the local environment, i.e. physical and chemical soil properties, in spring and autumn, while the density and diversity of plants had an additional effect in the summer period. Spatial relationships among plant and microbial communities were detected only in the early summer and autumn periods when aboveground biomass increase was most rapid and its influence on soil microbial communities was greatest due to increased demand by plants for nutrients. Individual properties exhibited varying degrees of spatial structure over the season. Differential responses of Gram positive and Gram negative bacterial communities to seasonal shifts in soil nutrients were detected. We concluded that spatial distribution patterns of soil microorganisms change over a season and that chemical soil properties are more important controlling factors than plant density and diversity. Finer spatial resolution, such as the mm to cm scale, as well as taxonomic resolution of microbial groups, could help determine the importance of plant species density, composition, and growth stage in shaping microbial community composition and spatial patterns. (C) 2014 The Authors. Published by Elsevier Ltd. All rights reserved.

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A 272-ha grove of dominant Microberlinia bisulcata (Caesalpinioideae) adult trees greater than or equal to 50 cm stem diameter was mapped in its entirety in the southern part of Korup National Park, Cameroon. The approach used an earlier-established 82.5-ha permanent plot with a new surrounding 50-m grid of transect lines. Tree diameters were available from the plot but trees on the grid were recorded as being greater than or equal to 50 cm. The grove consisted of 1028 trees in 2000. Other species occurred within the grove. including the associated subdominants Tetraberlinia bifoliolata and T. korupensis. Microberlinia bisulcata becomes adult at a stein diameter of c. 50 cm and at an estimated age of 50 y. Three oval-shaped subgroves with dimensions c. 8 50 in x 13 50 in (90 ha) were defined. For two of them (within the plot) tree diameters were available. Subgroves differed in their scales and intensities of spatial tree patterns, and in their size frequency distributions, these suggesting differing past dynamics. The modal scale of clumping was 40-50 m. Seed dispersal by pod ejection (to c. 50 in) was evident from the semi-circles of trees at the grove's edge and from the many internal circles (100-200 m diameter). The grove has the capacity. therefore, to increase at c. 100 m per century. To form its present extent and structure. it is inferred that it expanded and infilled from a possibly smaller area of lower adult-tree density. This possibly happened in three waves of recruitment, each one determined by a period of several intense disturbances. Climate records for Africa show that 1740-50 and 1820-30 were periods of drought, and that 1870-1895 was also regionally very dry. Canopy openings allow the light-demanding and fast-growing ectomycorrhizal M. bisulcata to establish, but successive releases are thought to be required to achieve effective recruitment. Nevertheless, in the last 50 y there were no major events and recruitment in the grove was very poor. This present study leads to a new hypothesis of the role of periods of multiple extreme events being the driving factor for the population dynamics of many large African tree species such as M. bisulcata.