[Noise analysis and optimization of spatial partition in functional imaging (author's transl)].
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Factor Analysis, Statistical↗
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Patterns of variation in a caste-cluster of Dhangars of Maharashtra, India.
We study patterns of variation among the 20 endogamous groups of Dhangars, a caste-cluster from Maharashtra State of India, who are semi-nomadic shepherds and cattle herders. To understand patterns of variation, we subjected the data on fourteen anthropometric measurements of about 2,500 adult males and data on 6 genetic markers, published among 13 of the 20 Dhangar castes, to R-matrix analysis, Harpending and Ward model of regression of heterozygosity on the distance from centroid of the populations, spatial autocorrelation analysis and Mantel statistics of matrix correspondence of the distances--geographic, anthropometric and genetic. Results of multiple regression analysis suggest a high degree of association between allele frequencies and the geographic longitude and latitude; R2 value suggests that about 70% of the variance in RH7 and ACP can be assigned to geographic distribution of groups. In case of anthropometry, this association with body size is found to be even stronger. Results of spatial autocorrelation analysis, as suggested by Moran's (I), are somewhat complementary to those based on multiple regression analysis. Mantel test indicates significant association between anthropometric distances and the geographic distances, not between geographic and genetic distances. The extent of differentiation of Dhangar sub-castes is much higher in anthropometric traits (F(ST) = 0.068) when compared to the genetic markers (F(ST) = 0.023). Yet, the F(ST) value obtained forgenetic markers is larger than the average for the Indian populations, based on similar class of markers. The positioning of the groups in the multivariate space reflects primarily geographic proximity of the groups with reference to anthropometric dimensions while no tangible pattern is evident forgenetic markers. The plot of average heterozygosity of the groups versus their distance from the gene frequency centroid seems to reflect population size variation, rather than group variation in external gene flow.
Adult↗
Hemispheric specialization for spatial frequency processing in the analysis of natural scenes.
Experimental data coming from visual cognitive sciences suggest that visual analysis starts with a parallel extraction of different visual attributes at different scales/frequencies. Neuropsychological and functional imagery data have suggested that each hemisphere (at the level of temporo-parietal junctions-TPJ) could play a key role in spatial frequency processing: The right TPJ should predominantly be involved in low spatial frequency (LFs) analysis and the left TPJ in high spatial frequency (HFs) analysis. Nevertheless, this functional hypothesis had been inferred from data obtained when using the hierarchical form paradigm, without any explicit spatial frequency manipulation per se. The aims of this research are (i) to investigate, in healthy subjects, the hemispheric asymmetry hypothesis with an explicit manipulation of spatial frequencies of natural scenes and (ii) to examine whether the 'precedence effect' (the relative rapidity of LFs and HFs processing) depends on the visual field of scene presentation or not. For this purpose, participants were to identify either non-filtered or LFs and HFs filtered target scene displayed either in the left, central, or right visual field. Results showed a hemispheric specialization for spatial frequency processing and different 'precedence effects' depending on the visual field of presentation.
Cognition↗
Analysis of temporal and spatial dichotomous PM air samples in the El Paso-Cd. Juarez air quality basin.
This paper presents and discusses the results obtained from the gravimetric and chemical analyses of the 24-hr average dichotomous samples collected from five sites in the El Paso-Cd. Juarez air quality basin between August 1999 and March 2000. Gravimetric analysis was performed to determine the temporal and spatial variations of PM2.5 (particulate matter less than 2.5 microm in diameter) and PM25-10 (particulate matter less than 10 pm but greater than 2.5 microm in diameter) mass concentrations. The results indicate that approximately 25% of the PM10 (i.e., PM25 + PM25-10) concentration is composed of PM2.5. Concurrent measurements of hourly PM concentrations and wind speed showed strong diurnal patterns of the regional PM pollution. Results of X-ray fluorescence (XRF) elemental analyses were compared to similar but limited studies performed by the Texas Natural Resource Conservation Commission (TNRCC) in 1990 and 1997. Major elements from geologic sources-Al, Si, Ca, Na, K, Fe, and Ti-accounted for 35% of the total mass concentrations in the PM2.5-10 fraction, indicating that geologic sources in the area are the dominant PM sources. Levels of toxic trace elements, mainly considered as products of anthropogenic activities, have decreased significantly from those observed in 1990 and 1997.
Air Pollutants↗
Stochastic analysis to assess the spatial distribution of groundwater nitrate concentrations in the Po catchment (Italy).
A large database including temporal trends of physical, ecological and socio-economic data was developed within the EUROCAT project. The aim was to estimate the nutrient fluxes for different socio-economic scenarios at catchment and coastal zone level of the Po catchment (Northern Italy) with reference to the Water Quality Objectives reported in the Water Framework Directive (WFD 2000/60/CE) and also in Italian legislation. Emission data derived from different sources at national, regional and local levels are referred to point and non-point sources. While non-point (diffuse) sources are simply integrated into the nutrient flux model, point sources are irregularly distributed. Intensive farming activity in the Po valley is one of the main Pressure factors Driving groundwater pollution in the catchment, therefore understanding the spatial variability of groundwater nitrate concentrations is a critical issue to be considered in developing a Water Quality Management Plan. In order to use the scattered point source data as input in our biogeochemical and transport models, it was necessary to predict their values and associated uncertainty at unsampled locations. This study reports the spatial distribution and uncertainty of groundwater nitrate concentration at a test site of the Po watershed using a probabilistic approach. Our approach was based on geostatistical sequential Gaussian simulation used to yield a series of stochastic images characterized by equally probable spatial distributions of the nitrate concentration across the area. Post-processing of many simulations allowed the mapping of contaminated and uncontaminated areas and provided a model for the uncertainty in the spatial distribution of nitrate concentrations.
Agriculture↗
Spatial dynamics of alcohol availability, neighborhood structure and violent crime.
OBJECTIVE: This study examined the relationship between neighborhood social structure, alcohol outlet densities and violent crime in Camden, New Jersey. METHOD: Data pertaining to neighborhood social structure, violent crime and alcohol density were collected for 98 block groups, and analyzed using bivariate, multivariate and spatial analyses. RESULTS: Each type of analysis showed that those areas with high alcohol outlet densities experienced more violent crime than low-density areas, after controlling for neighborhood social structure. In the multivariate regression analysis, alcohol outlet densities explained close to one fifth of the variability in violent crime rates across block groups--more than any one of the neighborhood structural variables included in the analysis. These findings were replicated in the spatial analysis, which also showed that alcohol outlet densities contributed significantly to violent crime within target block groups but not in adjacent block groups. CONCLUSIONS: High alcohol outlet density is associated with high rates of violent crime in this urban community. Spatial analysis suggests that alcohol outlets elevate the rate of violent crime within the immediate neighborhood context, not in surrounding neighborhoods.
Adolescent↗
Application of cluster analysis for characterization of spatial distribution of particles by stereological methods.
A method for the detection and characterization of clusters of particles observed in section with the electron microscope is presented. Cluster analysis is performed by the division method described by Berthet et al. (1976). Starting from a single cluster, profiles from each electron micrograph are successively classified in sets containing an increasing number of clusters. The decrease in the mean free distance, lambda, between profiles in the clusters, is used for terminating the subdivision procedure. The function relating the mean free distance with the number of clusters is evaluated in each subdivision set. The actual number of clusters is selected on the basis of the slope of that function, at a point where lambda has a value close to the average profile diameter. The method assumes a convex shape for the clusters; the salient feature is that it provides a physical delineation of clusters in the section. Hence, an evaluation of some characteristics of clusters in the three-dimensional sample may be obtained by using standard stereological procedures. Characterization of the volume to which the individual particles of a population are eventually restricted can as a result be performed. Practical problems in the acquisition of the data needed for cluster analysis are discussed and a system using for that purpose a Quantimet 720 image analyser in a basic configuration, connected on line with a PDP 11/10 minicomputer, is presented. Application of the method is illustrated by the analysis of lysosomes in cultured hepatoma (HTC) cells, at the end of mitosis and during the S phase. Cluster analysis shows that in cells actively synthesizing DNA they are grouped in clusters representing 5.7% of the cellular volume. Moreover, the average number of particles per cluster falls from a minimum of thirteen at mitosis to only six at the S phase.
Cells, Cultured↗
[Epidemiology of traffic accidents in the province of Trento: first results of an integrated surveillance system (MITRIS)].
OBJECTIVE: Different data sources are available for the surveillance of road traffic accidents. Taken separately all have important limits. Therefore the integration of medical and non medical data are essential for the construction of a surveillance system able to direct preventive and repressive actions. DESIGN: Cross sectional study. A computerized system for the rapid and precise unification of medical data with data collected by the police force has been realized. The model is embedded in a Geographic Information System (WebGIS), providing the facility for additional spatial data analysis and modelling. Maps of the spatial density of the accidents which consider also the severity of the injuries from a medical point of view have been developed. Risk factors associated with the severity of the injuries have been evaluated by uni- and multivariate statistical analysis. The statistical significance of the associations have been tested with Pearson's test. Confidential intervals of the Odds ratios were calculated with a probability of 95%. SETTING: Province of Trento, Italy. MAIN OUTCOME MEASURES: Number, dynamics and localization of road traffic accidents, activity of ambulance services, access to emergency departments and hospital admissions RESULTS: For 805/930 injured persons it was possible to link the medical data to those collected by the police forces. 111 (16%) accidents have been classified as severe (with hospital admission) and 694 as moderate (without hospital admission). The most important risk factors associated with the severity are represented by the frontal crash and by being a vulnerable road user (pedestrian, cyclist and motorcyclist), specially those <15 years of age. The classification of the most important sites of road traffic accidents in the Trento municipality was significantly modified by the integration of the medical data giving more importance to the more dangerous sites in terms of severity of the injuries. CONCLUSION: This study shows the feasibility of an integrated surveillance of road traffic accidents by using routinely collected data on a local basis.
Accidents, Traffic↗
Understanding spatial diagram structure: an analysis of hierarchies, matrices, and networks.
Abstract diagrams are powerful tools for comprehension and problem solving in diverse contexts. Two studies examined the structural properties of (i.e., applicability conditions for) three interrelated spatial diagrams--hierarchies, matrices, and networks. College students from two groups with distinct educational backgrounds and learning histories--advanced computer science students and representative undergraduates--rated the diagnosticity of the hypothesized applicability conditions for each of the 3 diagrams. The results validated 24-26 of the 30 hypothesized applicability conditions and provided evidence regarding the relative importance, or diagnosticity, of the validated properties for each type of diagram. A different set of properties was identified as most highly diagnostic for each type of diagram, indicating that the three spatial diagrams are optimized to serve different representational functions: The matrix stores static information about the kind of relation that exists between pairs of items in different sets, the network conveys dynamic information by showing the local connections and global routes connecting the items being represented, and the hierarchy depicts a rigid structure of power or precedence relations among items. The quantitative and qualitative differences in representational knowledge due to educational background are discussed.
Analysis of Variance↗
[Analysis of temporal and spatial changes of demographic structures in European countries by the principal components method].
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Demography↗
The structure of spatial ability items: a faceted analysis.
800 individuals were given a battery of 8 spatial tests which had been assembled with the aid of a mapping sentence of four content facets: rule type, dimensionality, presence or absence of rotation, and test format. An intercorrelation matrix of 49 items from these tests was analyzed by Smallest Space Analysis, SSA-I. All three facets formed distinct regions in a two-dimensional projection of a three-dimensional space. It is suggested that further facets be hypothesized to elaborate on the structure of spatial abilities.
Adolescent↗
Small-scale variability of metals in soil and composite sampling.
Soil pollution data is also strongly scattering at small scale. Sampling of composite samples, therefore, is recommended for pollution assessment. Different statistical methods are available to provide information about the accuracy of the sampling process. Autocorrelation and variogram analysis can be applied to investigate spatial relationships. Analysis of variance is a useful method for homogeneity testing. The main source of the total measurement uncertainty is the uncertainty arising from sampling. The sample mass required for analysis can also be estimated using an analysis of variance. The number of increments to be taken for a composite sample can be estimated by means of simple statistical formulae. Analytical results of composite samples obtained from different fusion procedures of increments can be compared by means of multiple mean comparison. The applicability of statistical methods and their advantages are demonstrated for a case study investigating metals in soil at a very small spatial scale. The paper describes important statistical tools for the quantitative assessment of the sampling process. Detailed results clearly depend on the purpose of sampling, the spatial scale of the object under investigation and the specific case study, and have to be determined for each particular case.
Environmental Monitoring↗
Utility of semivariogram for spatial variation of soil nutrients and the robust analysis of semivariogram.
The spatial variation of soil nutrients in topsoil (0-20 cm) was analyzed using semivariogram in the Zunhua County of Hebei Province, China. The effect on semivariogram with randomly deleted data and kriged estimates using various reduced sample sizes was also analyzed. The semivariograms of available N, total N, available P, organic matter were best described by a spherical model, except for available K, which best fitted a complex structure of exponential model and linear with sill model. The ratio of nugget to total sample variance ranged from 34.4% to 68.4%, indicating the spatial correlation of tested soil nutrients on a large scale was moderately dependent. Among five soil nutrients, available nitrogen and available phosphorus had the shortest spatial correlation range (5 km and 5.5 km), available K had the longest range (25.5 km), whereas total nitrogen and organic matter had intermediate spatial correlation range (14.5 km and 8.5 km). The semivariograms of available N, total N, available P, and organic matter were insensitive to a 50%-60% reduction in original sampling density, while for available K, it is up to 70%. The estimated spatial distributions of total N by kriging, under various reduced sample sizes, all correlated significantly (P = 0.001) with those obtained from original data. The results showed that the semivariogram was a relatively robust tool when used in a large region and sufficient spatial variation information could be retained regardless of a higher deletion proportion of the original data. The original sample data could be reduced by kriging and the estimates showed no loss of spatial information, however, the results may be unreliable unless a clearly identified semivariogram model could be obtained. The results may provide useful information for determining the appropriate sampling densities for these scales of soil survey.
Environmental Monitoring↗
Varieties of human spatial memory: a meta-analysis on the effects of hippocampal lesions.
The current meta-analysis included 27 studies on spatial-memory dysfunction in patients with hippocampal damage. Each study was classified on the basis of the task that was used, i.e., maze learning, working memory, object-location memory, or positional memory. The overall results demonstrated impairments on all spatial-memory tasks. Clear differences in effect size were found between positional memory on the one hand and maze learning, object-location memory, and working memory on the other hand. Lateralization was found only on maze learning and object-location memory. These findings clearly indicate that specific aspects of spatial memory can be affected in various degrees in patients with hippocampal lesions. Moreover, these results strongly support the notion that the hippocampus is important in the processing of metric positional information, probably in the form of an allocentric cognitive map.
Animals↗
Pattern perception at high velocities.
BACKGROUND: When objects are stationary, human pattern vision is exquisitely acute. A number of studies show, however, that Vernier acuity for lines is greatly impaired when the target velocity exceeds about 5 deg sec-1. The degradation of line Vernier acuity under image motion appears to be a consequence of a shift in the spatial scale of analysis to low spatial frequencies. If correct, this implies that Vernier acuity may not be subject to a strict velocity limit, and that with appropriate low spatial frequency stimuli, Vernier acuity might be preserved at high velocities. To test this notion, we measured Vernier acuity and contrast discrimination using low spatial frequency periodic gratings drifting over a wide range of velocities. RESULTS: Vernier acuity and contrast discrimination for low spatial frequency periodic gratings are both possible at velocities as high as 1000 deg sec-1. When both are specified in the same units (as Weber fractions), Vernier acuities are closely predicted by the observers' contrast discrimination thresholds. Our results suggest that Vernier acuity is subject to a spatiotemporal limit, rather than to a strict velocity limit. At temporal frequencies less than about 10 Hertz, Vernier acuity is independent of velocity, but is strongly dependent on stimulus contrast. At high temporal frequencies Vernier acuity is markedly degraded, and shows little dependence on contrast. CONCLUSIONS: Two mechanisms, which may have their neuronal counterparts early in the visual pathway, appear to limit the perception of moving targets at low and high temporal frequencies. Taken together with other recent work the present results suggest that the process of spatio-temporal interpolation in pattern analysis can operate at very high velocities.
Humans↗
Exploratory studies of PM10 receptor and source profiling by GC/MS and principal component analysis of temporally and spatially resolved ambient samples.
For a recent exploratory study of particulate matter (PM) compositions, origins, and impacts in the El Paso/Juarez (Paso del Norte) airshed, the authors relied on solvent extraction (SX)-gas chromatography/mass spectrometry (GC/MS) procedures to characterize 24-hr quartz fiber (QF) filter samples obtained from nine spatially distributed high-volume (Hi-Vol) PM10 samplers as well as on thermal desorption (TD)-GC/MS methods to characterize 45 time-resolved (2-hr) filter samples obtained with modified 1-m3/hr PM10 samplers. Principal component analysis and related chemometric techniques were used for data reduction and data fusion as well as for multiway data correlation. A high degree of correspondence (R2 = 0.821) was found between the rapid TD-GC/MS method (which can be carried out on 2-hr filter slices containing only microgram amounts of sample) and conventional SX-GC/MS procedures. The four main source patterns of organic PM components observed in GC/MS profiles of both temporally and spatially resolved receptor samples obtained in the El Paso/Juarez border airshed during the study period are interpreted to represent (1) vehicular emissions plus resuspended urban dust; (2) biomass combustion; (3) native vegetation detritus and resuspended agricultural dust; and (4) waste burning. Moreover, principal component analysis of combined, variance-weighted, temporally resolved TD-GC/MS data and spatially resolved SX-GC/MS data was used to determine approximate source locations for specific PM components identified in time-resolved receptor sample profiles. The same approach can be used to determine approximate circadian concentration profiles of specific PM components identified in spatially resolved receptor sample profiles.
Agriculture↗
Comparing the performance of two indices for spatial model selection: application to two mortality data.
The statistical analysis of spatially correlated data has become an important scientific research topic lately. The analysis of the mortality or morbidity rates observed at different areas may help to decide if people living in certain locations are considered at higher risk than others. Once the statistical model for the data of interest has been chosen, further effort can be devoted to identifying the areas under higher risks. Many scientists, including statisticians, have tried the conditional autoregressive (CAR) model to describe the spatial autocorrelation among the observed data. This model has greater smoothing effect than the exchangeable models, such as the Poisson gamma model for spatial data. This paper focuses on comparing the two types of models using the index LG, the ratio of local to global variability. Two applications, Taiwan asthma mortality and Scotland lip cancer, are considered and the use of LG is illustrated. The estimated values for both data sets are small, implying a Poisson gamma model may be favoured over the CAR model. We discuss the implications for the two applications respectively. To evaluate the performance of the index LG, we also compute the Bayes factor, a Bayesian model selection criterion, to see which model is preferred for the two applications and simulation data. To derive the value of LG, we estimate its posterior mode based on samples derived from the BUGS program, while for Bayes factor we use the double Laplace-Metropolis method, Schwarz criterion, and a modified harmonic mean for approximations. The results of LG and Bayes factor are consistent. We conclude that LG is fairly accurate as an index for selection between Poisson gamma and CAR model. When easy and fast computation is of concern, we recommend using LG as the first and less costly index.
Asthma↗
Texture analysis of cerebral white matter in SIV-infected macaque monkeys.
Image texture analysis is used in a wide variety of applications in medical research. Neurovirulent simian immunodeficiency virus (SIV) infection in monkeys is considered a good model for HIV-1 infection in humans and causes neuropathological changes in white matter which can include diffuse myelin pallor, subtle white matter astrocytosis, perivascular macrophage infiltrates, and microglial nodules with multinucleated giant cells. The ability of image texture analysis to quantify these changes was evaluated. Sections of thionin-stained brain tissue from eight male rhesus macaques ranging in age from 42-59 months were used. Four animals served as controls and four animals were infected with neurovirulent SIVmac239/17E-R71 by bone marrow inoculation. Images of cerebral white matter were captured and analyzed by calculating 13 textural features based on statistical analysis of spatial co-occurrence matrices. Statistical analysis of the results included multiple comparisons using the Newman-Keuls multiple range test. The effect of variation in background illumination used at image acquisition was also evaluated. Ten of the 13 textural features used in this study successfully discriminated between tissue from control and SIV-infected animals and were consistent with independent neuropathological assessment. Three textural features were highly sensitive to variation in background illumination and found not useful in this application.
Acquired Immunodeficiency Syndrome↗