956 resultados para Spatial Point Pattern analysis
Resumo:
An approach to incorporate spatial dependence into stochastic frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.
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Abstract: Movements away from the natal or home territory are important to many ecological processes, including gene flow, population regulation, and disease epidemiology, yet quantitative data on these behaviors are lacking. Red foxes exhibit 2 periods of extraterritorial movements: when an individual disperses and when males search neighboring territories for extrapair copulations during the breeding season. Using radiotracking data collected at 5-min interfix intervals, we compared movement parameters, including distance moved, speed of movement, and turning angles, of dispersal and reproductive movements to those made during normal territorial movements; the instantaneous separation distances of dispersing and extraterritorial movements to the movements of resident adults; and the frequency of locations of 95%, 60%, and 30% harmonic mean isopleths of adult fox home territories to randomly generated fox movements. Foxes making reproductive movements traveled farther than when undertaking other types of movement, and dispersal movements were straighter. Reproductive and dispersal movements were faster than territorial movements and also differed in intensity of search and thoroughness. Foxes making dispersal movements avoided direct contact with territorial adults and moved through peripheral areas of territories. The converse was true for reproductive movements. Although similar in some basic characteristics, dispersal and reproductive movements are fundamentally different both behaviorally and spatially and are likely to have different ultimate purposes and contrasting effects on spatial processes such as disease transmission
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Glycogen synthase kinase 3 (GSK3, of which there are two isoforms, GSK3alpha and GSK3beta) was originally characterized in the context of regulation of glycogen metabolism, though it is now known to regulate many other cellular processes. Phosphorylation of GSK3alpha(Ser21) and GSK3beta(Ser9) inhibits their activity. In the heart, emphasis has been placed particularly on GSK3beta, rather than GSK3alpha. Importantly, catalytically-active GSK3 generally restrains gene expression and, in the heart, catalytically-active GSK3 has been implicated in anti-hypertrophic signalling. Inhibition of GSK3 results in changes in the activities of transcription and translation factors in the heart and promotes hypertrophic responses, and it is generally assumed that signal transduction from hypertrophic stimuli to GSK3 passes primarily through protein kinase B/Akt (PKB/Akt). However, recent data suggest that the situation is far more complex. We review evidence pertaining to the role of GSK3 in the myocardium and discuss effects of genetic manipulation of GSK3 activity in vivo. We also discuss the signalling pathways potentially regulating GSK3 activity and propose that, depending on the stimulus, phosphorylation of GSK3 is independent of PKB/Akt. Potential GSK3 substrates studied in relation to myocardial hypertrophy include nuclear factors of activated T cells, beta-catenin, GATA4, myocardin, CREB, and eukaryotic initiation factor 2Bvarepsilon. These and other transcription factor substrates putatively important in the heart are considered. We discuss whether cardiac pathologies could be treated by therapeutic intervention at the GSK3 level but conclude that any intervention would be premature without greater understanding of the precise role of GSK3 in cardiac processes.
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By modelling the average activity of large neuronal populations, continuum mean field models (MFMs) have become an increasingly important theoretical tool for understanding the emergent activity of cortical tissue. In order to be computationally tractable, long-range propagation of activity in MFMs is often approximated with partial differential equations (PDEs). However, PDE approximations in current use correspond to underlying axonal velocity distributions incompatible with experimental measurements. In order to rectify this deficiency, we here introduce novel propagation PDEs that give rise to smooth unimodal distributions of axonal conduction velocities. We also argue that velocities estimated from fibre diameters in slice and from latency measurements, respectively, relate quite differently to such distributions, a significant point for any phenomenological description. Our PDEs are then successfully fit to fibre diameter data from human corpus callosum and rat subcortical white matter. This allows for the first time to simulate long-range conduction in the mammalian brain with realistic, convenient PDEs. Furthermore, the obtained results suggest that the propagation of activity in rat and human differs significantly beyond mere scaling. The dynamical consequences of our new formulation are investigated in the context of a well known neural field model. On the basis of Turing instability analyses, we conclude that pattern formation is more easily initiated using our more realistic propagator. By increasing characteristic conduction velocities, a smooth transition can occur from self-sustaining bulk oscillations to travelling waves of various wavelengths, which may influence axonal growth during development. Our analytic results are also corroborated numerically using simulations on a large spatial grid. Thus we provide here a comprehensive analysis of empirically constrained activity propagation in the context of MFMs, which will allow more realistic studies of mammalian brain activity in the future.
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Using a model calibrated to Khao Yai National Park in Thailand, this paper highlights the importance of generating explicitly spatial and temporal data for developing management plans for tropical protected forests. Spatial and temporal cost-benefit analysis should account for the interactions between different land uses – such as the benefits of contiguous areas of preserved land and edge effects – and the realities of villagers living near forests who rely on extracted resources. By taking a temporal perspective, this paper provides a rare empirical assessment of the importance of quasi-option values when determining optimal management plans.
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Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.
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Climate models taking part in the coupled model intercomparison project phase 5 (CMIP5) all predict a global mean sea level rise for the 21st century. Yet the sea level change is not spatially uniform and differs among models. Here we evaluate the role of air–sea fluxes of heat, water and momentum (windstress) to find the spatial pattern associated to each of them as well as the spread they can account for. Using one AOGCM to which we apply the surface flux changes from other AOGCMs, we show that the heat flux and windstress changes dominate both the pattern and the spread, but taking the freshwater flux into account as well yields a sea level change pattern in better agreement with the CMIP5 ensemble mean. Differences among the CMIP5 control ocean temperature fields have a smaller impact on the sea level change pattern.
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Predictions of twenty-first century sea level change show strong regional variation. Regional sea level change observed by satellite altimetry since 1993 is also not spatially homogenous. By comparison with historical and pre-industrial control simulations using the atmosphere–ocean general circulation models (AOGCMs) of the CMIP5 project, we conclude that the observed pattern is generally dominated by unforced (internal generated) variability, although some regions, especially in the Southern Ocean, may already show an externally forced response. Simulated unforced variability cannot explain the observed trends in the tropical Pacific, but we suggest that this is due to inadequate simulation of variability by CMIP5 AOGCMs, rather than evidence of anthropogenic change. We apply the method of pattern scaling to projections of sea level change and show that it gives accurate estimates of future local sea level change in response to anthropogenic forcing as simulated by the AOGCMs under RCP scenarios, implying that the pattern will remain stable in future decades. We note, however, that use of a single integration to evaluate the performance of the pattern-scaling method tends to exaggerate its accuracy. We find that ocean volume mean temperature is generally a better predictor than global mean surface temperature of the magnitude of sea level change, and that the pattern is very similar under the different RCPs for a given model. We determine that the forced signal will be detectable above the noise of unforced internal variability within the next decade globally and may already be detectable in the tropical Atlantic.
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The hippocampus plays a pivotal role in the formation and consolidation of episodic memories, and in spatial orientation. Historically, the adult hippocampus has been viewed as a very static anatomical region of the mammalian brain. However, recent findings have demonstrated that the dentate gyrus of the hippocampus is an area of tremendous plasticity in adults, involving not only modifications of existing neuronal circuits, but also adult neurogenesis. This plasticity is regulated by complex transcriptional networks, in which the transcription factor NF-κB plays a prominent role. To study and manipulate adult neurogenesis, a transgenic mouse model for forebrain-specific neuronal inhibition of NF-κB activity can be used. In this study, methods are described for the analysis of NF-κB-dependent neurogenesis, including its structural aspects, neuronal apoptosis and progenitor proliferation, and cognitive significance, which was specifically assessed via a dentate gyrus (DG)-dependent behavioral test, the spatial pattern separation-Barnes maze (SPS-BM). The SPS-BM protocol could be simply adapted for use with other transgenic animal models designed to assess the influence of particular genes on adult hippocampal neurogenesis. Furthermore, SPS-BM could be used in other experimental settings aimed at investigating and manipulating DG-dependent learning, for example, using pharmacological agents.
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This paper analyses the impact of several avoided deforestation policies within a patchy forested landscape. Central is the idea that deforestation choices in one area influence deforestation decisions in nearby patches. We explore the interplay between forest landscapes comprising heterogeneous patches, localised spatial displacement, and avoided deforestation policies. Avoided deforestation policies at a landscape level are respectively: two Payments for Environmental Services (PES) policies, one focused on deforestation hotspots, the second being equally available to all agents; a conservation area; and, an agglomeration bonus. We demonstrate how the "best" policy, in terms of reduced leakage, depends on landscape heterogeneity. Agglomeration bonuses are shown to be more effective where there is less landscape heterogeneity, whilst conservation areas are most effective where there is more spatial heterogeneity.
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Little research so far has been devoted to understanding the diffusion of grassroots innovation for sustainability across space. This paper explores and compares the spatial diffusion of two networks of grassroots innovations, the Transition Towns Network (TTN) and Gruppi di Acquisto Solidale (Solidarity Purchasing Groups – GAS), in Great Britain and Italy. Spatio-temporal diffusion data were mined from available datasets, and patterns of diffusion were uncovered through an exploratory data analysis. The analysis shows that GAS and TTN diffusion in Italy and Great Britain is spatially structured, and that the spatial structure has changed over time. TTN has diffused differently in Great Britain and Italy, while GAS and TTN have diffused similarly in central Italy. The uneven diffusion of these grassroots networks on the one hand challenges current narratives on the momentum of grassroots innovations, but on the other highlights important issues in the geography of grassroots innovations for sustainability, such as cross-movement transfers and collaborations, institutional thickness, and interplay of different proximities in grassroots innovation diffusion.
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Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.
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Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r2 = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r2 = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.
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This study aims at the determination of a Fram Strait cyclone track and of the cyclone’s impact on ice edge, drift, divergence, and concentration. A 24 h period on 13–14 March 2002 framed by two RADARSAT images is analyzed. Data are included from autonomous ice buoys, a research vessel, Special Sensor Microwave Imager (SSM/I) and QuikSCAT satellite, and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) model. During this 24 h period the cyclone moved northward along the western ice edge in the Fram Strait, crossed the northern ice edge, made a left-turn loop with 150 km diameter over the sea ice, and returned to the northern ice edge. The ECMWF analysis places the cyclone track 100 km too far west over the sea ice, a deviation which is too large for representative sea ice simulations. On the east side of the northward moving cyclone, the ice edge was pushed northward by 55 km because of strong winds. On the rear side, the ice edge advanced toward the open water but by a smaller distance because of weaker winds there. The ice drift pattern as calculated from the ice buoys and the two RADARSAT images is cyclonically curved around the center of the cyclone loop. Ice drift divergence shows a spatial pattern with divergence in the loop center and a zone of convergence around. Ice concentration changes as retrieved from SSM/I data follow the divergence pattern such that sea ice concentration increased in areas of divergence and decreased in areas of convergence.
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A detailed study was performed for a sample of low-mass pre-main-sequence (PMS) stars, previously identified as weak-line T Tauri stars, which are compared to members of the Tucanae and Horologium Associations. Aiming to verify if there is any pattern of abundances when comparing the young stars at different phases, we selected objects in the range from 1 to 100 Myr, which covers most of PMS evolution. High-resolution optical spectra were acquired at European Southern Observatory and Observatorio do Pico dos Dias. The stellar fundamental parameters effective temperature and gravity were calculated by excitation and ionization equilibria of iron absorption lines. Chemical abundances were obtained via equivalent width calculations and spectral synthesis for 44 per cent of the sample, which shows metallicities within 0.5 dex solar. A classification was developed based on equivalent width of Li I 6708 angstrom and Ha lines and spectral types of the studied stars. This classification allowed a separation of the sample into categories that correspond to different evolutive stages in the PMS. The position of these stars in the Hertzsprung-Russell diagram was also inspected in order to estimate their ages and masses. Among the studied objects, it was verified that our sample actually contains seven weak-line T Tauri stars, three are Classical T Tauri, 12 are Fe/Ge PMS stars and 21 are post-T Tauri or young main-sequence stars. An estimation of circumstellar luminosity was obtained using a disc model to reproduce the observed spectral energy distribution. Most of the stars show low levels of circumstellar emission, corresponding to less than 30 per cent of the total emission.