857 resultados para Management Misperceptions: An Obstacle to Motivation


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La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

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This special issue gathers together a number of recent papers on fractal geometry and its applications to the modeling of flow and transport in porous media. The aim is to provide a systematic approach for analyzing the statics and dynamics of fluids in fractal porous media by means of theory, modeling and experimentation. The topics covered include lacunarity analyses of multifractal and natural grayscale patterns, random packing's of self-similar pore/particle size distributions, Darcian and non-Darcian hydraulic flows, diffusion within fractals, models for the permeability and thermal conductivity of fractal porous media and hydrophobicity and surface erosion properties of fractal structures.

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In this study we apply count data models to four integer–valued time series related to accidentality in Spanish roads applying both the frequentist and Bayesian approaches. The time series are: number of fatalities, number of fatal accidents, number of killed or seriously injured (KSI) and number of accidents with KSI. The model structure is Poisson regression with first order autoregressive errors. The purpose of the paper is first to sort out the explanatory variables by relevance and second to carry out a prediction exercise for validation.

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Most red wines commercialized in the market use the malolactic fermentationprocess in order to ensure stability from a microbiological point of view. In this secondfermentation, malic acid is converted into L-lactic acid under controlled setups. Howeverthis process is not free from possible collateral effects that on some occasions produceoff-flavors, wine quality loss and human health problems. In warm viticulture regions suchas the south of Spain, the risk of suffering a deviation during the malolactic fermentationprocess increases due to the high must pH. This contributes to produce wines with highvolatile acidity and biogenic amine values. This manuscript develops a new red winemakingmethodology that consists of combining the use of two non-Saccharomyces yeast strains asan alternative to the traditional malolactic fermentation. In this method, malic acid is totallyconsumed by Schizosaccharomyces pombe, thus achieving the microbiological stabilizationobjective, while Lachancea thermotolerans produces lactic acid in order not to reduce andeven increase the acidity of wines produced from low acidity musts. This technique reducesthe risks inherent to the malolactic fermentation process when performed in warm regions.The result is more fruity wines that contain less acetic acid and biogenic amines than thetraditional controls that have undergone the classical malolactic fermentation.

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Se ha presentado la evaluación y optimización de las reglas de operación de un embalse para gestión de avenidas usando un entorno integrado hidrológico- hidráulico de tipo Monte Carlo. Some reservoirs play a major role in flood protection, managing the floods and reducing or delaying the peak discharges in the river downstream. However, the changing environment (natural and anthropological changes) requires the development of more elaborated strategies for reservoir operation. Three factors are relevant: 1) the natural variability of inflow hydrographs, 2) the competition for reservoir storage capacity between flood control and other uses, and 3) the existence of built-up areas on downstream river reaches. A framework for evaluation/optimization of reservoir operation rules for flood management in a changing environment is presented in this study. The study was carried out using an integrated hydrologic – hydraulic model in a Monte Carlo framework.

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Concentrating Solar Power (CSP) plants typically incorporate one or various auxiliary boilers operating in parallel to the solar field to facilitate start up operations, provide system stability, avoid freezing of heat transfer fluid (HTF) and increase generation capacity. The environmental performance of these plants is highly influenced by the energy input and the type of auxiliary fuel, which in most cases is natural gas (NG). Replacing the NG with biogas or biomethane (BM) in commercial CSP installations is being considered as a means to produce electricity that is fully renewable and free from fossil inputs. Despite their renewable nature, the use of these biofuels also generates environmental impacts that need to be adequately identified and quantified. This paper investigates the environmental performance of a commercial wet-cooled parabolic trough 50 MWe CSP plant in Spain operating according to two strategies: solar-only, with minimum technically viable energy non-solar contribution; and hybrid operation, where 12 % of the electricity derives from auxiliary fuels (as permitted by Spanish legislation). The analysis was based on standard Life Cycle Assessment (LCA) methodology (ISO 14040-14040). The technical viability and the environmental profile of operating the CSP plant with different auxiliary fuels was evaluated, including: NG; biogas from an adjacent plant; and BM withdrawn from the gas network. The effect of using different substrates (biowaste, sewage sludge, grass and a mix of biowaste with animal manure) for the production of the biofuels was also investigated. The results showed that NG is responsible for most of the environmental damage associated with the operation of the plant in hybrid mode. Replacing NG with biogas resulted in a significant improvement of the environmental performance of the installation, primarily due to reduced impact in the following categories: natural land transformation, depletion of fossil resources, and climate change. However, despite the renewable nature of the biofuels, other environmental categories like human toxicity, eutrophication, acidification and marine ecotoxicity scored higher when using biogas and BM.

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Neuronal morphology is hugely variable across brain regions and species, and their classification strategies are a matter of intense debate in neuroscience. GABAergic cortical interneurons have been a challenge because it is difficult to find a set of morphological properties which clearly define neuronal types. A group of 48 neuroscience experts around the world were asked to classify a set of 320 cortical GABAergic interneurons according to the main features of their three-dimensional morphological reconstructions. A methodology for building a model which captures the opinions of all the experts was proposed. First, one Bayesian network was learned for each expert, and we proposed an algorithm for clustering Bayesian networks corresponding to experts with similar behaviors. Then, a Bayesian network which represents the opinions of each group of experts was induced. Finally, a consensus Bayesian multinet which models the opinions of the whole group of experts was built. A thorough analysis of the consensus model identified different behaviors between the experts when classifying the interneurons in the experiment. A set of characterizing morphological traits for the neuronal types was defined by performing inference in the Bayesian multinet. These findings were used to validate the model and to gain some insights into neuron morphology.

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The incidence of Amaranthaceae pollen allergy has increased due to the desertification occurring in many countries. In some regions of Spain, Salsola kali is the main cause of pollinosis, at almost the same level as olive and grass pollen. Sal k 1 - the sensitization marker of S. kali pollinosis - is used in clinical diagnosis, but is purified at a low yield from pollen. We aimed to produce a recombinant (r)Sal k 1 able to span the structural and immunological properties of the natural isoforms from pollen, and validate its potential use for diagnosis. METHODS: Specific cDNA was amplified by PCR, cloned into the pET41b vector and used to transform BL21 (DE3) Escherichia coli cells. Immunoblotting, ELISA, basophil activation and skin-prick tests were used to validate the recombinant protein against Sal k 1 isolated from pollen. Sera and blood cells from S. kali pollen-sensitized patients and specific monoclonal and polyclonal antisera were used. RESULTS: rSal k 1 was produced in bacteria with a yield of 7.5 mg/l of cell culture. The protein was purified to homogeneity and structural and immunologically validated against the natural form. rSal k 1 exhibited a higher IgE cross-reactivity with plant-derived food extracts such as peanut, almond or tomato than with pollen sources such as Platanus acerifolia and Oleaceae members. CONCLUSIONS: rSal k 1 expressed in bacteria retains intact structural and immunological properties in comparison to the pollen-derived allergen. It spans the immunological properties of most of the isoforms found in pollen, and it might substitute natural Sal k 1 in clinical diagnosis.

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Ancient septicemic plague epidemics were reported to have killed millions of people for 2 millenniums. However, confident diagnosis of ancient septicemia solely on the basis of historical clinical observations is not possible. The lack of suitable infected material has prevented direct demonstration of ancient septicemia; thus, the history of most infections such as plague remains hypothetical. The durability of dental pulp, together with its natural sterility, makes it a suitable material on which to base such research. We hypothesized that it would be a lasting refuge for Yersinia pestis, the plague agent. DNA extracts were made from the dental pulp of 12 unerupted teeth extracted from skeletons excavated from 16th and 18th century French graves of persons thought to have died of plague (“plague teeth”) and from 7 ancient negative control teeth. PCRs incorporating ancient DNA extracts and primers specific for the human β-globin gene demonstrated the absence of inhibitors in these preparations. The incorporation of primers specific for Y. pestis rpoB (the RNA polymerase β-subunit-encoding gene) and the recognized virulence-associated pla (the plasminogen activator-encoding gene) repeatedly yielded products that had a nucleotide sequence indistinguishable from that of modern day isolates of the bacterium. The specific pla sequence was obtained from 6 of 12 plague skeleton teeth but 0 of 7 negative controls (P < 0.034, Fisher exact test). A nucleic acid-based confirmation of ancient plague was achieved for historically identified victims, and we have confirmed the presence of the disease at the end of 16th century in France. Dental pulp is an attractive target in the quest to determine the etiology of septicemic illnesses detected in ancient corpses. Molecular techniques could be applied to this material to resolve historical outbreaks.

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The vitamin K-dependent γ-glutamyl carboxylase catalyzes the posttranslational conversion of glutamic acid to γ-carboxyglutamic acid in precursor proteins containing the γ-carboxylation recognition site (γ-CRS). During this reaction, glutamic acid is converted to γ-carboxyglutamic acid while vitamin KH2 is converted to vitamin K 2,3-epoxide. Recombinant bovine carboxylase was purified free of γ-CRS-containing propeptide and endogenous substrate in a single-step immunoaffinity procedure. We show that in the absence of γ-CRS-containing propeptide and/or glutamate-containing substrate, carboxylase has little or no epoxidase activity. Epoxidase activity is induced by Phe-Leu-Glu-Glu-Leu (FLEEL) (9.2 pmol per min per pmol of enzyme), propeptide, residues −18 to −1 of proFactor IX (3.4 pmol per min per pmol of enzyme), FLEEL and propeptide (100 pmol per min per pmol of enzyme), and proPT28 (HVFLAPQQARSLLQRVRRANTFLEEVRK, residues −18 to +10 of human acarboxy-proprothrombin), (5.3 pmol per min per pmol of enzyme). These results indicate that in the absence of propeptide or glutamate-containing substrate, oxygenation of vitamin K by the carboxylase does not occur. Upon addition of propeptide or glutamate-containing substrate, the enzyme is converted to an active epoxidase. This regulatory mechanism prevents the generation of a highly reactive vitamin K intermediate in the absence of a substrate for carboxylation.

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The effect of atmospheric aerosols and regional haze from air pollution on the yields of rice and winter wheat grown in China is assessed. The assessment is based on estimates of aerosol optical depths over China, the effect of these optical depths on the solar irradiance reaching the earth’s surface, and the response of rice and winter wheat grown in Nanjing to the change in solar irradiance. Two sets of aerosol optical depths are presented: one based on a coupled, regional climate/air quality model simulation and the other inferred from solar radiation measurements made over a 12-year period at meteorological stations in China. The model-estimated optical depths are significantly smaller than those derived from observations, perhaps because of errors in one or both sets of optical depths or because the data from the meteorological stations has been affected by local pollution. Radiative transfer calculations using the smaller, model-estimated aerosol optical depths indicate that the so-called “direct effect” of regional haze results in an ≈5–30% reduction in the solar irradiance reaching some of China’s most productive agricultural regions. Crop-response model simulations suggest an ≈1:1 relationship between a percentage increase (decrease) in total surface solar irradiance and a percentage increase (decrease) in the yields of rice and wheat. Collectively, these calculations suggest that regional haze in China is currently depressing optimal yields of ≈70% of the crops grown in China by at least 5–30%. Reducing the severity of regional haze in China through air pollution control could potentially result in a significant increase in crop yields and help the nation meet its growing food demands in the coming decades.