Spatial patterns mediated by subcritical and supercritical thermal fluctuations in the splay Fréedericksz transition

The magnetically induced splay Fréedericksz transition is reexamined to look for pattern forming phenomena slightly above or below criticality. By using our traditional scheme of stochastic nematodynamic equations, situations are, respectively, found of transient and permanent predominance of transversal periodicities (wave numbers) along the direction perpendicular to the initial orientation within the sample. The relevance of these predictions in relation with recent observations in the electrically driven splay Fréedericksz transition, and in general with other pattern forming phenomena, is stressed.

aIr-1, a newly found locus on mouse chromosome 16 encoding a trans-acting activator factor for MHC class II gene expression.

RJ 2.2.5 is a human B cell line that has lost the capacity to express MHC class II genes. The human class II-positive phenotype is restored in somatic cell hybrids between RJ 2.2.5 and mouse spleen cells. By karyotype and molecular studies of an informative family of hybrids we have now shown that the reexpression of human class II gene products, as well as the maintenance of the mouse class II-positive phenotype, correlates with the presence of mouse chromosome 16. Thus, the existence on this mouse chromosome of a newly found locus, designated by us aIr-1, that determines a trans-acting activator function for class II gene expression, is established. Possible implications of this finding are discussed.

Public health expenditure and spatial interactions in a decentralized national health system

One of the limitations of cross-country health expenditure analysis refers to the fact that the financing, the internal organization and political restraints of health care decision-making are country-specific and heterogeneous. Yet, a potential solution is to examine the influence of such effects in those countries that have undertaken decentralization processes. In such a setting, it is possible to examine potential expenditure spillovers across the geography of a country as well as the influence of the political ideology of regional incumbents on public health expenditure. This paper examines the determinants of public health expenditure within Spanish region-states (Autonomous Communities, ACs), most of them subject to similar financing structures although exhibiting significant heterogeneity as a result of the increasing decentralization, region-specific political factors along with different use of health care inputs, economic dimension and spatial interactions

Influence of bedrock structures on the spatial pattern of erosional landforms in small alpine catchments

Structural settings and lithological characteristics are traditionally assumed to influence the development of erosional landforms, such as gully networks and rock couloirs, in steep mountain rock basins. The structural control of erosion of two small alpine catchments of distinctive rock types is evaluated by comparing the correspondences between the orientations of their gullies and rock couloirs with (1) the sliding orientations of potential slope failures mechanisms, and (2) the orientation of the maximum joint frequency, this latter being considered as the direction exploited primarily by erosion and mass wasting processes. These characteristic orientations can be interpreted as structural weaknesses contributing to the initiation and propagation of erosion. The morphostructural analysis was performed using digital elevation models and field observations. The catchment comprised of magmatic intrusive rocks shows a clear structural control, mostly expressed through potential wedges failure. Such joint configurations have a particular geometry that encourages the development of gullies in hard rock, e.g. through enhanced gravitational and hydrological erosional processes. In the catchment underlain by sedimentary rocks, penetrative joints that act as structural weaknesses seem to be exploited by gullies and rock couloirs. However, the lithological setting and bedding configuration prominently control the development of erosional landforms, and influence not only the local pattern of geomorphic features, but the general morphology of the catchment. The orientations of the maximum joint frequency are clearly associated with the gully network, suggesting that its development is governed by anisotropy in rock strength. These two catchments are typical of bedrock-dominated basins prone to intense processes of debris supply. This study suggests a quantitative approach for describing the relationship between bedrock jointing and geomorphic features geometry. Incorporation of bedrock structure can be relevant when studying processes governing the transfer of clastic material, for the assessment of sediment yields and in landforms evolution models.

New Developments and Applications of the MP2RAGE Sequence - Focusing the Contrast and High Spatial Resolution R1 Mapping.

MR structural T1-weighted imaging using high field systems (>3T) is severely hampered by the existing large transmit field inhomogeneities. New sequences have been developed to better cope with such nuisances. In this work we show the potential of a recently proposed sequence, the MP2RAGE, to obtain improved grey white matter contrast with respect to conventional T1-w protocols, allowing for a better visualization of thalamic nuclei and different white matter bundles in the brain stem. Furthermore, the possibility to obtain high spatial resolution (0.65 mm isotropic) R1 maps fully independent of the transmit field inhomogeneities in clinical acceptable time is demonstrated. In this high resolution R1 maps it was possible to clearly observe varying properties of cortical grey matter throughout the cortex and observe different hippocampus fields with variations of intensity that correlate with known myelin concentration variations.

What drives invasibility? A multi-model inference test and spatial modelling of alien plant species richness patterns in northern Portugal

Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.

Spatial relational learning and memory abilities do not differ between men and women in a real-world, open-field environment

This study assesses gender differences in spatial and non-spatial relational learning and memory in adult humans behaving freely in a real-world, open-field environment. In Experiment 1, we tested the use of proximal landmarks as conditional cues allowing subjects to predict the location of rewards hidden in one of two sets of three distinct locations. Subjects were tested in two different conditions: (1) when local visual cues marked the potentially-rewarded locations, and (2) when no local visual cues marked the potentially-rewarded locations. We found that only 17 of 20 adults (8 males, 9 females) used the proximal landmarks to predict the locations of the rewards. Although females exhibited higher exploratory behavior at the beginning of testing, males and females discriminated the potentially-rewarded locations similarly when local visual cues were present. Interestingly, when the spatial and local information conflicted in predicting the reward locations, males considered both spatial and local information, whereas females ignored the spatial information. However, in the absence of local visual cues females discriminated the potentially-rewarded locations as well as males. In Experiment 2, subjects (9 males, 9 females) were tested with three asymmetrically-arranged rewarded locations, which were marked by local cues on alternate trials. Again, females discriminated the rewarded locations as well as males in the presence or absence of local cues. In sum, although particular aspects of task performance might differ between genders, we found no evidence that women have poorer allocentric spatial relational learning and memory abilities than men in a real-world, open-field environment.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Expression of genes encoding cytotoxic cell-associated serine proteases in thymocytes.

A family of homologous serine esterases designated granzyme A-H and the pore-forming protein perforin are present in cytoplasmic granules of mature peripheral cytolytic T lymphocytes and natural killer cells. In vivo, the majority of cytotoxic T cells containing these granule-associated proteins are of the CD4-CD8+ phenotype. It is generally assumed that these cells are derived from immature CD4-CD8- thymocytes. However, the precise intrathymic differentiation steps leading to functionally mature cytotoxic T cells are unclear. Thus we decided to analyze the expression of genes in the thymus which are preferentially expressed in mature cytotoxic cells, i.e. granzyme A, granzyme B, and perforin. In situ hybridization on tissue sections revealed the expression of genes coding for granzyme A and granzyme B in the thymus. No evidence was found, however, for thymocytes expressing the perforin gene. Granzyme A and granzyme B mRNA positive cells in the thymus are almost exclusively CD4-CD8- thymocytes, particularly of the CD3- IL2R- phenotype.

Structure and spatial variability of Pinus uncinata Ram. growth forms at two contrasting treeline ecotones in the Spanish Pyrenees.

Describimos la distribución espacial de individuos de Pinus uncinata clasificados según su forma de crecimiento y tamaño en dos ecotonos poco perturbados del límite altitudinal del árbol situados en los Pirineos Centrales españoles (Ordesa, O; Tessó, T). En cada sitio situamos una parcela rectangular (30 140 m), que incluía los límites del árbol y del bosque, y cuyo lado mayor seguía el gradiente altitudinal. En ambos sitios, los individuos vivos eran más grandes y tenían un mayor número de cohortes de acículas pendiente abajo. La distribución de las clases de individuos según su forma de crecimiento y tamaño en el sitio O seguía una secuencia de mayor tamaño pendiente abajo, desde abundantes individuos policórmicos arbustivos (krummholz) con pocas cohortes de acículas (1-3) hasta individuos arbóreos mayores unicórmicos con varias cohortes de acículas (4-12). Por el contrario, los cambios estructurales en el ecotono del sitio T fueron graduales y no siguieron de forma tan clara dicha secuencia

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Spatial distribution and biomass of aquatic rooted macrophytes and their relevance in the metabolism of a Mediterranean coastal lagoon

This work aims to characterise the current autotrophic compartment of the Albufera des Grau coastal lagoon (Menorca, Balearic Islands) and to assess the relationship between the submerged macrophytes and the limnological parameters of the lagoon. During the study period the submerged vegetation was dominated by the macrophyte Ruppia cirrhosa, which formed dense extensive meadows covering 79% of the surface. Another macrophyte species, Potamogeton pectinatus, was also observed but only forming small stands near the rushing streams. Macroalgae were only occasionally observed. Macrophyte biomass showed a clear seasonal trend, with maximum values in July. The biomass of R. cirrhosa achieved 1760 g DW m-2, the highest biomass ever reported for this species in the literature. The seasonal production-decomposition cycle of the macrophyte meadows appears to drive the nutrient dynamics and carbon fluxes in the lagoon. Despite the significant biomass accumulation and the absence of a washout of nutrients and organic matter to the sea, the lagoon did not experience a dystrophic collapse. These results indicate that internal metabolism is more important than exchange processes in the lagoon.