885 resultados para Spatial R-DBMS, Miniere italiane, GIS, depositi sterili


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Because of the high number of crashes occurring on highways, it is necessary to intensify the search for new tools that help in understanding their causes. This research explores the use of a geographic information system (GIS) for an integrated analysis, taking into account two accident-related factors: design consistency (DC) (based on vehicle speed) and available sight distance (ASD) (based on visibility). Both factors require specific GIS software add-ins, which are explained. Digital terrain models (DTMs), vehicle paths, road centerlines, a speed prediction model, and crash data are integrated in the GIS. The usefulness of this approach has been assessed through a study of more than 500 crashes. From a regularly spaced grid, the terrain (bare ground) has been modeled through a triangulated irregular network (TIN). The length of the roads analyzed is greater than 100 km. Results have shown that DC and ASD could be related to crashes in approximately 4% of cases. In order to illustrate the potential of GIS, two crashes are fully analyzed: a car rollover after running off road on the right side and a rear-end collision of two moving vehicles. Although this procedure uses two software add-ins that are available only for ArcGIS, the study gives a practical demonstration of the suitability of GIS for conducting integrated studies of road safety.

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La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.

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The present study used functional magnetic resonance imaging to demonstrate that performance of visual spatial and visual nonspatial working memory tasks involve the same regions of the lateral prefrontal cortex when all factors unrelated to the type of stimulus material are appropriately controlled. These results provide evidence that spatial and nonspatial working memory may not be mediated, respectively, by mid-dorsolateral and mid-ventrolateral regions of the frontal lobe, as widely assumed, and support the alternative notion that specific regions of the lateral prefrontal cortex make identical executive functional contributions to both spatial and nonspatial working memory.

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This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), (2851ERA01J). FT and RPR were supported by FACCE MACSUR (3200009600) through the Finnish Ministry of Agriculture and Forestry (MMM). EC, HE and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences) and thank professor P-E Jansson (Royal Institute of Technology, Stockholm) for support. JC, HR and DW thank the INRA ACCAF metaprogramm for funding and Eric Casellas from UR MIAT INRA for support. CB was funded by the Helmholtz project “REKLIM—Regional Climate Change”. CK was funded by the HGF Alliance “Remote Sensing and Earth System Dynamics” (EDA). FH was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) under the Grant FOR1695. FE and SS acknowledge support by the German Science Foundation (project EW 119/5-1). HH, GZ, SS, TG and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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ACKNOWLEDGMENTS MW and RVD have been supported by the German Federal Ministry for Education and Research (BMBF) via the Young Investigators Group CoSy-CC2 (grant no. 01LN1306A). JFD thanks the Stordalen Foundation and BMBF (project GLUES) for financial support. JK acknowledges the IRTG 1740 funded by DFG and FAPESP. MT Gastner is acknowledged for providing his data on the airline, interstate, and Internet network. P Menck thankfully provided his data on the Scandinavian power grid. We thank S Willner on behalf of the entire zeean team for providing the data on the world trade network. All computations have been performed using the Python package pyunicorn [41] that is available at https://github.com/pik-copan/pyunicorn.

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Funded by Energy Technologies Institute EPSRC-Supergen. Grant Number: EP/M013200/1

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8 pages, 2 figures, to be published in the conference proceedings of 11th international conference "Computer Data Analysis & Modeling 2016"

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The myristoylated alanine-rich C kinase substrate (MARCKS) is a prominent protein kinase C (PKC) substrate in brain that is expressed highly in hippocampal granule cells and their axons, the mossy fibers. Here, we examined hippocampal infrapyramidal mossy fiber (IP-MF) limb length and spatial learning in heterozygous Macs mutant mice that exhibit an ≈50% reduction in MARCKS expression relative to wild-type controls. On a 129B6(N3) background, the Macs mutation produced IP-MF hyperplasia, a significant increase in hippocampal PKCɛ expression, and proficient spatial learning relative to wild-type controls. However, wild-type 129B6(N3) mice exhibited phenotypic characteristics resembling inbred 129Sv mice, including IP-MF hypoplasia relative to inbred C57BL/6J mice and impaired spatial-reversal learning, suggesting a significant contribution of 129Sv background genes to wild-type and possibly mutant phenotypes. Indeed, when these mice were backcrossed with inbred C57BL/6J mice for nine generations to reduce 129Sv background genes, the Macs mutation did not effect IP-MF length or hippocampal PKCɛ expression and impaired spatial learning relative to wild-type controls, which now showed proficient spatial learning. Moreover, in a different strain (B6SJL(N1), the Macs mutation also produced a significant impairment in spatial learning that was reversed by transgenic expression of MARCKS. Collectively, these data indicate that the heterozygous Macs mutation modifies the expression of linked 129Sv gene(s), affecting hippocampal mossy fiber development and spatial learning performance, and that MARCKS plays a significant role in spatial learning processes.

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During mouse embryogenesis, two waves of hematopoietic progenitors originate in the yolk sac. The first wave consists of primitive erythroid progenitors that arise at embryonic day 7.0 (E7.0), whereas the second wave consists of definitive erythroid progenitors that arise at E8.25. To determine whether these unilineage hematopoietic progenitors arise from multipotential precursors, we investigated the kinetics of high proliferative potential colony-forming cells (HPP-CFC), multipotent precursors that give rise to macroscopic colonies when cultured in vitro. No HPP-CFC were found at presomite stages (E6.5–E7.5). Rather, HPP-CFC were detected first at early somite stages (E8.25), exclusively in the yolk sac. HPP-CFC were found subsequently in the bloodstream at higher levels than the remainder of the embryo proper. However, the yolk sac remains the predominant site of HPP-CFC expansion (>100-fold) until the liver begins to serve as the major hematopoietic organ at E11.5. On secondary replating, embryonic HPP-CFC give rise to definitive erythroid and macrophage (but not primitive erythroid) progenitors. Our findings support the hypothesis that definitive but not primitive hematopoietic progenitors originate from yolk sac-derived HPP-CFC during late gastrulation.

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Volumetric studies in a range of animals (London taxi-drivers, polygynous male voles, nest-parasitic female cowbirds, and a number of food-storing birds) have shown that the size of the hippocampus, a brain region essential to learning and memory, is correlated with tasks involving an extra demand for spatial learning and memory. In this paper, we report the quantitative advantage that food storers gain from such an enlargement. Coal tits (Parus ater) a food-storing species, performed better than great tits (Parus major), a nonstoring species, on a task that assessed memory persistence but not on a task that assessed memory resolution or on one that tested memory capacity. These results show that the advantage to the food-storing species associated with an enlarged hippocampus is one of memory persistence.

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Hippocampal neuron loss is widely viewed as a hallmark of normal aging. Moreover, neuronal degeneration is thought to contribute directly to age-related deficits in learning and memory supported by the hippocampus. By taking advantage of improved methods for quantifying neuron number, the present study reports evidence challenging these long-standing concepts. The status of hippocampal-dependent spatial learning was evaluated in young and aged Long-Evans rats using the Morris water maze, and the total number of neurons in the principal cell layers of the dentate gyrus and hippocampus was quantified according to the optical fractionator technique. For each of the hippocampal fields, neuron number was preserved in the aged subjects as a group and in aged individuals with documented learning and memory deficits indicative of hippocampal dysfunction. The findings demonstrate that hippocampal neuronal degeneration is not an inevitable consequence of normal aging and that a loss of principal neurons in the hippocampus fails to account for age-related learning and memory impairment. The observed preservation of neuron number represents an essential foundation for identifying the neurobiological effects of hippocampal aging that account for cognitive decline.

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The selective activation of the prefrontal cortical dopamine system by mild stress can be mimicked by anxiogenic beta-carbolines such as FG7142. To investigate the functional relevance of elevated levels of dopamine turnover in the prefrontal cortex, the current study examined the effects of FG7142 on the performance of spatial working memory tasks in the rat and monkey. FG7142 selectively increased prefrontal cortical dopamine turnover in rats and significantly impaired performance on spatial working memory tasks in both rats and monkeys. Spatial discrimination, a task with similar motor and motivational demands (rats), or delayed response performance following zero-second delays (monkeys) was unaffected by FG7142. Further, biochemical analysis in rats revealed a significant positive correlation between dopamine turnover in the prefrontal cortex and cognitive impairment on the delayed alternation task. The cognitive deficits in both rats and monkeys were prevented by pretreatment with the benzodiazepine receptor antagonist, RO15-1788, which blocked the increase in dopamine turnover and by the dopamine receptor antagonists, haloperidol, clozapine, and SCH23390. These findings indicate that excessive dopamine activity in the prefrontal cortex is detrimental to cognitive functions mediated by the prefrontal cortex.

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We have determined the volume and location of hippocampal tissue required for normal acquisition of a spatial memory task. Ibotenic acid was used to make bilateral symmetric lesions of 20-100% of hippocampal volume. Even a small transverse block (minislab) of the hippocampus (down to 26% of the total) could support spatial learning in a water maze, provided it was at the septal (dorsal) pole of the hippocampus. Lesions of the septal pole, leaving 60% of the hippocampi intact, caused a learning deficit, although normal electrophysiological responses, synaptic plasticity, and preserved acetylcholinesterase staining argue for adequate function of the remaining tissue. Thus, with an otherwise normal brain, hippocampal-dependent spatial learning only requires a minislab of dorsal hippocampal tissue.

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The visual stimuli that elicit neural activity differ for different retinal ganglion cells and these cells have been categorized by the visual information that they transmit. If specific visual information is conveyed exclusively or primarily by a particular set of ganglion cells, one might expect the cells to be organized spatially so that their sampling of information from the visual field is complete but not redundant. In other words, the laterally spreading dendrites of the ganglion cells should completely cover the retinal plane without gaps or significant overlap. The first evidence for this sort of arrangement, which has been called a tiling or tessellation, was for the two types of "alpha" ganglion cells in cat retina. Other reports of tiling by ganglion cells have been made subsequently. We have found evidence of a particularly rigorous tiling for the four types of ganglion cells in rabbit retina that convey information about the direction of retinal image motion (the ON-OFF direction-selective cells). Although individual cells in the four groups are morphologically indistinguishable, they are organized as four overlaid tilings, each tiling consisting of like-type cells that respond preferentially to a particular direction of retinal image motion. These observations lend support to the hypothesis that tiling is a general feature of the organization of information outflow from the retina and clearly implicate mechanisms for recognition of like-type cells and establishment of mutually acceptable territories during retinal development.