Efficient knowledge retrieval to calibrate input variables in forest fire prediction

Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a robust and efficient knowledge storage and retrieval method. Nearest neighbour search is applied to find the fire configuration from knowledge base most similar to the current configuration. Therefore, a distance measure was elaborated and implemented in several ways. Experiments show the performance of the different implementations regarding occupied storage and retrieval time with overly satisfactory results.

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Angiotensinergic innervation of the kidney: present knowledge and its significance.

Intrarenal neurotransmission implies the co-release of neuropeptides at the neuro-effector junction with direct influence on parameters of kidney function. The presence of an angiotensin (Ang) II-containing phenotype in catecholaminergic postganglionic and sensory fibers of the kidney, based on immunocytological investigations, has only recently been reported. These angiotensinergic fibers display a distinct morphology and intrarenal distribution, suggesting anatomical and functional subspecialization linked to neuronal Ang II-expression. This review discusses the present knowledge concerning these fibers, and their significance for renal physiology and the pathogenesis of hypertension in light of established mechanisms. The data suggest a new role of Ang II as a co-transmitter stimulating renal target cells or modulating nerve traffic from or to the kidney. Neuronal Ang II is likely to be an independent source of intrarenal Ang II. Further physiological experimentation will have to explore the role of the angiotensinergic renal innervation and integrate it into existing concepts.

The Impact of Higher Education Institution-Firm Knowledge Links on Firm-level Productivity in Britain

This paper estimates whether both sourcing knowledge from and/or cooperating on innovation with HEIs (Higher Education Institutions)1 impacts on establishment-level total factor productivity (TFP) using a dataset created by merging the UK government’s Community Innovation Survey (CIS) with the Annual Respondents Database (ARD). It also considers whether higher graduate employment (as a measure of human capital) also impacts positively on TFP at the establishment-level. Many studies have investigated the relationship between university-firm knowledge links and innovation (see, for example, Mansfield, 1991; Becker, 2003; Thorn et al, 2007). Most of these studies find a positive impact. Fewer studies have investigated the impact of university-firm knowledge links on productivity. Belderbos et al. (2004), using the Dutch CIS, find that cooperation with universities has no statistically significant impact on the growth of labour productivity. Medda et al. (2005) find no statistically significant effect of collaborative research undertaken by Italian manufacturing firms and universities on the growth of TFP. Arvanitis et al. (2008), using Swiss data, show that university-firm knowledge and technology transfer has both a direct impact on labour productivity and an indirect impact through its positive impact on innovation. In sum, there is as yet no clear consensus as to the impact of university-firm knowledge links on productivity.

Which prior knowledge? Quantification of in vivo brain 13C MR spectra following 13C glucose infusion using AMARES.

The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.

Non-cooperative incentives to share knowledge in competitive environments

In this paper we study a model where non-cooperative agents may exchange knowledge in a competitive environment. As a potential factor that could induce the knowledge disclosure between humans we consider the timing of the moves of players. We develop a simple model of a multistage game in which there are only three players and competition takes place only within two stages. Players can share their private knowledge with their opponents and the knowledge is modelled as in uencing their marginal cost of e¤ort. We identify two main mechanisms that work towards knowledge disclosure. One of them is that before the actual competition starts, the stronger player of the rst stage of a game may have desire to share his knowledge with the "observer", be- cause this reduces the valuation of the prize of the weaker player of that stage and as a result his e¤ort level and probability of winning in a ght. Another mechanism is that the "observer" may have sometimes desire to share knowledge with the weaker player of the rst stage, because in this way, by increasing his probability of winning in that stage, he decreases the probability of winning of the stronger player. As a result, in the second stage the "observer" may have greater chances to meet the weaker player rather than the stronger one. Keywords: knowledge sharing, strategic knowledge disclosure, multistage contest game, non-cooperative games

Codex Search: propuesta e implementación de un sistema de recuperación de información de ámbito local basado en casos

CODEX SEARCH es un motor de recuperación de información especializado en derecho de extranjería que está basado en herramientas y conocimiento lingüísticos. Un motor o Sistema de Recuperación de Información (SRI) es un software capaz de localizar información en grandes colecciones documentales (entorno no trivial) en formato electrónico. Mediante un estudio previo se ha detectado que la extranjería es un ámbito discursivo en el que resulta difícil expresar la necesidad de información en términos de una consulta formal, objeto de los sistemas de recuperación actuales. Por lo tanto, para desarrollar un SRI eficiente en el dominio indicado no basta con emplear un modelo tradicional de RI, es decir, comparar los términos de la pregunta con los de la respuesta, básicamente porque no expresan implicaciones y porque no tiene que haber necesariamente una relación 1 a 1. En este sentido, la solución lingüística propuesta se basa en incorporar el conocimiento del especialista mediante la integración en el sistema de una librería de casos. Los casos son ejemplos de procedimientos aplicados por expertos a la solución de problemas que han ocurrido en la realidad y que han terminado en éxito o fracaso. Los resultados obtenidos en esta primera fase son muy alentadores pero es necesario continuar la investigación en este campo para mejorar el rendimiento del prototipo al que se puede acceder desde &http://161.116.36.139/~codex/&.

Historiografía occidental y mitología prehispánica en la novela histórica latinoamericana

Hacia fines del siglo XX, en Latinoamérica se publica una gran producción de novelas calificadas como históricas, notable cuantitativa y cualitativamente. Sus novedosas propuestas y las diferencias que guarda respecto a las características tradicionales del género, provocan un cuestionamiento crítico respecto a la categoría de novela histórica. En general, las producciones recientes problematizan las posibilidades del conocimiento histórico, como también las posibilidades del lenguaje para expresar ese conocimiento. Además, contienen una fuerte crítica hacia el discurso historiográfico oficial y recurren a la historia, no como producto acabado o dato, sino como procedimiento narrativo y cognoscitivo. Esto les permite trascender la referencia histórica local –sin excluirla – para remitir de manera más amplia a la historiografía y a la historia como portadores de la verdad sobre el pasado. La investigación analiza un corpus de novelas argentinas de finales del siglo pasado indagando los conceptos de historia y ficción propuestos por los textos.

Effects of Experience, Knowledge and Signals on Willingness to Pay for a Public Good

This paper compares how increases in experience versus increases in knowledge about a public good affect willingness to pay (WTP) for its provision. This is challenging because while consumers are often certain about their previous experiences with a good, they may be uncertain about the accuracy of their knowledge. We therefore design and conduct a field experiment in which treated subjects receive a precise and objective signal regarding their knowledge about a public good before estimating their WTP for it. Using data for two different public goods, we show qualitative equivalence of the effect of knowledge and experience on valuation for a public good. Surprisingly, though, we find that the causal effect of objective signals about the accuracy of a subject’s knowledge for a public good can dramatically affect their valuation for it: treatment causes an increase of $150-$200 in WTP for well-informed individuals. We find no such effect for less informed subjects. Our results imply that WTP estimates for public goods are not only a function of true information states of the respondents but beliefs about those information states.

Partial Knowledge Restrictions on theTwo-Stage Threshold Model of Choice

In the context of the two-stage threshold model of decision making, with the agent’s choices determined by the interaction Of three “structural variables,” we study the restrictions on behavior that arise when one or more variables are xogenously known. Our results supply necessary and sufficient conditions for consistency with the model for all possible states of partial Knowledge, and for both single- and multivalued choice functions.

Traditional Chinese materia medica: a retrospect and prospect

For thousands of years, traditional medicine and remedies have been practed and used in the fight against disease in China. They have proved to be valuable and the distillate of vast historical experience based on field-tested human experiments, long-term observations and clinical trials. The Chinese people belive that traditional medicine is consistent with theirown culture. Endowed with a unique theoretical system and provided outstanding clinical results, traditional Chinese medicine continues to play an important role in helping the Chinese nation flourish. The recent study of traditional medicinal plants in Chine has given us confidence that what was recorded in ancient medical literature through empirical observations is indeed still coindicent with the concepts of modern chemistry, pharmacology and medicine. The task of revealing what is valid and efficacious should be retained, and what is mythic and invalid should be discarded in traditional Chinese medicine may require scientific research lasting for several generations. Therfore, multidisciplinary cooperation and international collaboration in this field would be essential. Systematic coordination of work in traditional medicine by word organizations, national governments, private foundations and individual scientists is a requisite as well.

Plants used in traditional medicine of China and Brazil

Eventhough the rationale behind the use of medicinal plantes in Brazil and Chine is different, twenty four species are used in both countries. Scientific name, vulgar name and uses in both countries along with their chemical constituents are listed.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.