935 resultados para point-to-segment algorithm


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Bruynooghe described a framework for the top-down abstract interpretation of logic programs. In this framework, abstract interpretation is carried out by constructing an abstract and-or tree in a top-down fashion for a given query and program. Such an abstract interpreter requires fixpoint computation for programs which contain recursive predicates. This paper presents in detail a fixpoint algorithm that has been developed for this purpose and the motivation behind it. We start off by describing a simple-minded algorithm. After pointing out its shortcomings, we present a series of refinements to this algorithm, until we reach the final version. The aim is to give an intuitive grasp and provide justification for the relative complexity of the final algorithm. We also present an informal proof of correctness of the algorithm and some results obtained from an implementation.

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En esta tesis se presenta una nueva aproximación para la realización de mapas de calidad del aire, con objeto de que esta variable del medio físico pueda ser tenida en cuenta en los procesos de planificación física o territorial. La calidad del aire no se considera normalmente en estos procesos debido a su composición y a la complejidad de su comportamiento, así como a la dificultad de contar con información fiable y contrastada. Además, la variabilidad espacial y temporal de las medidas de calidad del aire hace que sea difícil su consideración territorial y exige la georeferenciación de la información. Ello implica la predicción de medidas para lugares del territorio donde no existen datos. Esta tesis desarrolla un modelo geoestadístico para la predicción de valores de calidad del aire en un territorio. El modelo propuesto se basa en la interpolación de las medidas de concentración de contaminantes registradas en las estaciones de monitorización, mediante kriging ordinario, previa homogeneización de estos datos para eliminar su carácter local. Con el proceso de eliminación del carácter local, desaparecen las tendencias de las series muestrales de datos debidas a las variaciones temporales y espaciales de la calidad del aire. La transformación de los valores de calidad del aire en cantidades independientes del lugar de muestreo, se realiza a través de parámetros de uso del suelo y de otras variables características de la escala local. Como resultado, se obtienen unos datos de entrada espacialmente homogéneos, que es un requisito fundamental para la utilización de cualquier algoritmo de interpolación, en concreto, del kriging ordinario. Después de la interpolación, se aplica una retransformación de los datos para devolver el carácter local al mapa final. Para el desarrollo del modelo, se ha elegido como área de estudio la Comunidad de Madrid, por la disponibilidad de datos reales. Estos datos, valores de calidad del aire y variables territoriales, se utilizan en dos momentos. Un momento inicial, donde se optimiza la selección de los parámetros más adecuados para la eliminación del carácter local de las medidas y se desarrolla cada una de las etapas del modelo. Y un segundo momento, en el que se aplica en su totalidad el modelo desarrollado y se contrasta su eficacia predictiva. El modelo se aplica para la estimación de los valores medios y máximos de NO2 del territorio de estudio. Con la implementación del modelo propuesto se acomete la territorialización de los datos de calidad del aire con la reducción de tres factores clave para su efectiva integración en la planificación territorial o en el proceso de toma de decisiones asociado: incertidumbre, tiempo empleado para generar la predicción y recursos (datos y costes) asociados. El modelo permite obtener una predicción de valores del contaminante objeto de análisis en unas horas, frente a los periodos de modelización o análisis requeridos por otras metodologías. Los recursos necesarios son mínimos, únicamente contar con los datos de las estaciones de monitorización del territorio que, normalmente, están disponibles en las páginas web viii institucionales de los organismos gestores de las redes de medida de la calidad del aire. Por lo que respecta a las incertidumbres de la predicción, puede decirse que los resultados del modelo propuesto en esta tesis son estadísticamente muy correctos y que los errores medios son, en general, similares o menores que los encontrados con la aplicación de las metodologías existentes. ABSTRACT This thesis presents a new approach for mapping air quality, so that this variable of physical environment can be taken into account in physical or territorial planning. Ambient air quality is not normally considered in territorial planning mainly due to the complexity of its composition and behavior and the difficulty of counting with reliable and contrasted information. In addition, the wide spatial and temporal variability of the measurements of air quality makes his territorial consideration difficult and requires georeferenced information. This involves predicting measurements in the places of the territory where there are no data. This thesis develops a geostatistical model for predicting air quality values in a territory. The proposed model is based on the interpolation of measurements of pollutants from the monitoring stations, using ordinary kriging, after a detrending or removal of the local character of sampling values process. With the detrending process, the local character of the time series of sampling data, due to temporal and spatial variations of air quality, is removed. The transformation of the air quality values into site-independent quantities is performed using land use parameters and other characteristic parameters of local scale. This detrending of the monitoring data process results in a spatial homogeneous input set which is a prerequisite for a correct use of any interpolation algorithm, particularly, ordinary kriging. After the interpolation step, a retrending or retransformation is applied in order to incorporate the local character in the final map at places where no monitoring data is available. For the development of this model, the Community of Madrid is chosen as study area, because of the availability of actual data. These data, air quality values and local parameters, are used in two moments. A starting point, to optimize the selection of the most suitable indicators for the detrending process and to develop each one of the model stages. And a second moment, to fully implement the developed model and to evaluate its predictive power. The model is applied to estimate the average and maximum values of NO2 in the study territory. With the implementation of the proposed model, the territorialization of air quality data is undertaken with the reduction in three key factors for the effective integration of this parameter in territorial planning or in the associated decision making process: uncertainty, time taken to generate the prediction and associated resources (data and costs). This model allows the prediction of pollutant values in hours, compared to the implementation time periods required for other modeling or analysis methodologies. The required resources are also minimal, only having data from monitoring stations in the territory, that are normally available on institutional websites of the authorities responsible for air quality networks control and management. With regard to the prediction uncertainties, it can be concluded that the results of the proposed model are statistically very accurate and the mean errors are generally similar to or lower than those found with the application of existing methodologies.

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Collaborative efforts between the Neutronics and Target Design Group at the Instituto de Fusión Nuclear and the Molecular Spectroscopy Group at the ISIS Pulsed Neutron and Muon Source date back to 2012 in the context of the ESS-Bilbao project. The rationale for these joint activities was twofold, namely: to assess the realm of applicability of the low-energy neutron source proposed by ESS-Bilbao - for details; and to explore instrument capabilities for pulsed-neutron techniques in the range 0.05-3 ms, a time range where ESS-Bilbao and ISIS could offer a significant degree of synergy and complementarity. As part of this collaboration, J.P. de Vicente has spent a three-month period within the ISIS Molecular Spectroscopy Group, to gain hands-on experience on the practical aspects of neutron-instrument design and the requisite neutron-transport simulations. To date, these activities have resulted in a joint MEng thesis as well as a number of publications and contributions to national and international conferences. Building upon these previous works, the primary aim of this report is to provide a self-contained discussion of general criteria for instrument selection at ESS-Bilbao, the first accelerator-driven, low-energy neutron source designed in Spain. To this end, Chapter 1 provides a brief overview of the current design parameters of the accelerator and target station. Neutron moderation is covered in Chapter 2, where we take a closer look at two possible target-moderator-reflector configurations and pay special attention to the spectral and temporal characteristics of the resulting neutron pulses. This discussion provides a necessary starting point to assess the operation of ESSB in short- and long-pulse modes. These considerations are further explored in Chapter 3, dealing with the primary characteristics of ESS-Bilbao as a short- or long-pulse facility in terms of accessible dynamic range and spectral resolution. Other practical aspects including background suppression and the use of fast choppers are also discussed. The guiding principles introduced in the first three chapters are put to use in Chapter 4 where we analyse in some detail the capabilities of a small-angle scattering instrument, as well as how specific scientific requirements can be mapped onto the optimal use of ESS-Bilbao for condensed-matter research. Part 2 of the report contains additional supporting documentation, including a description of the ESSB McStas component, a detailed characterisation of moderator response and neutron pulses, and estimates ofparameters associated with the design and operation of neutron choppers. In closing this brief foreword, we wish to thank both ESS-Bilbao and ISIS for their continuing encouragement and support along the way.

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La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.

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Amidases [EC 3.5.1.4] capable of converting indole-3-acetamide (IAM) into the major plant growth hormone indole-3-acetic acid (IAA) are assumed to be involved in auxin de novo biosynthesis. With the emerging amount of genomics data, it was possible to identify over forty proteins with substantial homology to the already characterized amidases from Arabidopsis and tobacco. The observed high conservation of amidase-like proteins throughout the plant kingdom may suggest an important role of theses enzymes in plant development. Here, we report cloning and functional analysis of four, thus far, uncharacterized plant amidases from Oryza sativa, Sorghum bicolor, Medicago truncatula, and Populus trichocarpa. Intriguingly, we were able to demonstrate that the examined amidases are also capable of converting phenyl-2-acetamide (PAM) into phenyl-2-acetic acid (PAA), an auxin endogenous to several plant species including Arabidopsis. Furthermore, we compared the subcellular localization of the enzymes to that of Arabidopsis AMI1, providing further evidence for similar enzymatic functions. Our results point to the presence of a presumably conserved pathway of auxin biosynthesis via IAM, as amidases, both of monocot, and dicot origins, were analyzed.

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Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

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Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

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The European Union has been promoting linguistic diversity for many years as one of its main educational goals. This is an element that facilitates student mobility and student exchanges between different universities and countries and enriches the education of young undergraduates. In particular,a higher degree of competence in the English language is becoming essential for engineers, architects and researchers in general, as English has become the lingua franca that opens up horizons to internationalisation and the transfer of knowledge in today’s world. Many experts point to the Integrated Approach to Contents and Foreign Languages System as being an option that has certain benefits over the traditional method of teaching a second language that is exclusively based on specific subjects. This system advocates teaching the different subjects in the syllabus in a language other than one’s mother tongue, without prioritising knowledge of the language over the subject. This was the idea that in the 2009/10 academic year gave rise to the Second Language Integration Programme (SLI Programme) at the Escuela Arquitectura Tecnica in the Universidad Politecnica Madrid (EUATM-UPM), just at the beginning of the tuition of the new Building Engineering Degree, which had been adapted to the European Higher Education Area (EHEA) model. This programme is an interdisciplinary initiative for the set of subjects taught during the semester and is coordinated through the Assistant Director Office for Educational Innovation. The SLI Programme has a dual goal; to familiarise students with the specific English terminology of the subject being taught, and at the same time improve their communication skills in English. A total of thirty lecturers are taking part in the teaching of eleven first year subjects and twelve in the second year, with around 120 students who have voluntarily enrolled in a special group in each semester. During the 2010/2011 academic year the degree of acceptance and the results of the SLI Programme are being monitored. Tools have been designed to aid interdisciplinary coordination and to analyse satisfaction, such as coordination records and surveys. The results currently available refer to the first semester of the year and are divided into specific aspects of the different subjects involved and into general aspects of the ongoing experience.

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Anastigmatic imaging of an object to an image surfaces without the point-to-point mapping prescription and using a single optical surface is analyzed in 2D and 3D geometries (free-form and rotational-symmetric). Several design techniques are shown.

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In a Finite Element (FE) analysis of elastic solids several items are usually considered, namely, type and shape of the elements, number of nodes per element, node positions, FE mesh, total number of degrees of freedom (dot) among others. In this paper a method to improve a given FE mesh used for a particular analysis is described. For the improvement criterion different objective functions have been chosen (Total potential energy and Average quadratic error) and the number of nodes and dof's of the new mesh remain constant and equal to the initial FE mesh. In order to find the mesh producing the minimum of the selected objective function the steepest descent gradient technique has been applied as optimization algorithm. However this efficient technique has the drawback that demands a large computation power. Extensive application of this methodology to different 2-D elasticity problems leads to the conclusion that isometric isostatic meshes (ii-meshes) produce better results than the standard reasonably initial regular meshes used in practice. This conclusion seems to be independent on the objective function used for comparison. These ii-meshes are obtained by placing FE nodes along the isostatic lines, i.e. curves tangent at each point to the principal direction lines of the elastic problem to be solved and they should be regularly spaced in order to build regular elements. That means ii-meshes are usually obtained by iteration, i.e. with the initial FE mesh the elastic analysis is carried out. By using the obtained results of this analysis the net of isostatic lines can be drawn and in a first trial an ii-mesh can be built. This first ii-mesh can be improved, if it necessary, by analyzing again the problem and generate after the FE analysis the new and improved ii-mesh. Typically, after two first tentative ii-meshes it is sufficient to produce good FE results from the elastic analysis. Several example of this procedure are presented.

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Hybrid mice carrying oncogenic transgenes afford powerful systems for investigating loss of heterozygosity (LOH) in tumors. Here, we apply this approach to a neoplasm of key importance in human medicine: mammary carcinoma. We performed a whole genome search for LOH using the mouse mammary tumor virus/v-Ha-ras mammary carcinoma model in female (FVB/N × Mus musculus castaneus)F1 mice. Mammary tumors developed as expected, as well as a few tumors of a second type (uterine leiomyosarcoma) not previously associated with this transgene. Genotyping of 94 anatomically independent tumors revealed high-frequency LOH (≈38%) for markers on chromosome 4. A marked allelic bias was observed, with M. musculus castaneus alleles almost exclusively being lost. No evidence of genomic imprinting effects was noted. These data point to the presence of a tumor suppressor gene(s) on mouse chromosome 4 involved in mammary carcinogenesis induced by mutant H-ras expression, and for which a significant functional difference may exist between the M. musculus castaneus and FVB/N alleles. Provisional subchromosomal localization of this gene, designated Loh-3, can be made to a distal segment having syntenic correspondence to human chromosome 1p; LOH in this latter region is observed in several human malignancies, including breast cancers. Evidence was also obtained for a possible second locus associated with LOH with less marked allele bias on proximal chromosome 4.

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Benzodiazepines allosterically modulate γ-aminobutyric acid (GABA) evoked chloride currents of γ-aminobutyric acid type A (GABAA) receptors. Coexpression of either rat γ2 or γ3, in combination with α1 and β2 subunits, results both in receptors displaying high [3H]Ro 15-1788 affinity. However, receptors containing a γ3 subunit display a 178-fold reduced affinity to zolpidem as compared with γ2-containing receptors. Eight chimeras between γ2 and γ3 were constructed followed by nine different point mutations in γ2, each to the homologous amino acid residue found in γ3. Chimeric or mutant γ subunits were coexpressed with α1 and β2 in human embryonic kidney 293 cells to localize amino acid residues responsible for the reduced zolpidem affinity. Substitution of a methionine-to-leucine at position 130 of γ2 (γ2M130L) resulted in a 51-fold reduction in zolpidem affinity whereas the affinity to [3H]Ro 15-1788 remained unchanged. The affinity for diazepam was only decreased by about 2-fold. The same mutation resulted in a 9-fold increase in Cl 218872 affinity. A second mutation (γ2M57I) was found to reduce zolpidem affinity by about 4-fold. Wild-type and γ2M130L-containing receptors were functionally expressed in Xenopus oocytes. Upon mutation allosteric coupling between agonist and modulatory sites is preserved. Dose–response curves for zolpidem and for diazepam showed that the zolpidem but not the diazepam apparent affinity is drastically reduced. The apparent GABA affinity is not significantly affected by the γ2M130L mutation. The identified amino acid residues may define part of the benzodiazepine binding pocket of GABAA receptors. As the modulatory site in the GABAA receptor is homologous to the GABA site, and to all agonist sites of related receptors, γ2M130 may either point to a homologous region important for agonist binding in all receptors or define a new region not underlying this principle.

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By using a simplified model of small open liquid-like clusters with surface effects, in the gas phase, it is shown how the statistical thermodynamics of small systems can be extended to include metastable supersaturated gaseous states not too far from the gas–liquid equilibrium transition point. To accomplish this, one has to distinguish between mathematical divergence and physical convergence of the open-system partition function.

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The comparison of malaria indicators among populations that have different genetic backgrounds and are uniformly exposed to the same parasite strains is one approach to the study of human heterogeneities in the response to the infection. We report the results of comparative surveys on three sympatric West African ethnic groups, Fulani, Mossi, and Rimaibé, living in the same conditions of hyperendemic transmission in a Sudan savanna area northeast of Ouagadougou, Burkina Faso. The Mossi and Rimaibé are Sudanese negroid populations with a long tradition of sedentary farming, while the Fulani are nomadic pastoralists, partly settled and characterized by non-negroid features of possible caucasoid origin. Parasitological, clinical, and immunological investigations showed consistent interethnic differences in Plasmodium falciparum infection rates, malaria morbidity, and prevalence and levels of antibodies to various P. falciparum antigens. The data point to a remarkably similar response to malaria in the Mossi and Rimaibé, while the Fulani are clearly less parasitized, less affected by the disease, and more responsive to all antigens tested. No difference in the use of malaria protective measures was demonstrated that could account for these findings, and sociocultural or environmental factors do not seem to be involved. Known genetic factors of resistance to malaria did not show higher frequencies in the Fulani. The differences in the immune response were not explained by the entomological observations, which indicated substantially uniform exposure to infective bites. The available data support the existence of unknown genetic factors, possibly related to humoral immune responses, determining interethnic differences in the susceptibility to malaria.

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In coming decades, global climate changes are expected to produce large shifts in vegetation distributions at unprecedented rates. These shifts are expected to be most rapid and extreme at ecotones, the boundaries between ecosystems, particularly those in semiarid landscapes. However, current models do not adequately provide for such rapid effects—particularly those caused by mortality—largely because of the lack of data from field studies. Here we report the most rapid landscape-scale shift of a woody ecotone ever documented: in northern New Mexico in the 1950s, the ecotone between semiarid ponderosa pine forest and piñon–juniper woodland shifted extensively (2 km or more) and rapidly (<5 years) through mortality of ponderosa pines in response to a severe drought. This shift has persisted for 40 years. Forest patches within the shift zone became much more fragmented, and soil erosion greatly accelerated. The rapidity and the complex dynamics of the persistent shift point to the need to represent more accurately these dynamics, especially the mortality factor, in assessments of the effects of climate change.