239 resultados para ISING-MODELS
A priori parameterisation of the CERES soil-crop models and tests against several European data sets
Resumo:
Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.
Resumo:
Mushroom picking has become a widespread autumn recreational activity in the Central Pyrenees and other regions of Spain. Predictive models that relate mushroom production or fungal species richness with forest stand and site characteristics are not available. This study used mushroom production data from 24 Scots pine plots over 3 years to develop a predictive model that could facilitate forest management decisions when comparing silvicultural options in terms of mushroom production. Mixed modelling was used to model the dependence of mushroom production on stand and site factors. The results showed that productions were greatest when stand basal area was approximately 20 m2 ha-1. Increasing elevation and northern aspect increased total mushroom production as well as the production of edible and marketed mushrooms. Increasing slope decreased productions. Marketed Lactarius spp., the most important group collected in the region, showed similar relationships. The annual variation in mushroom production correlated with autumn rainfall. Mushroom species richness was highest when the total production was highest.
Resumo:
The present study tests the relationships between the three frequently used personality models evaluated by the Temperament Character Inventory-Revised (TCI-R), Neuroticism Extraversion Openness Five Factor Inventory – Revised (NEO-FFI-R) and Zuckerman-Kuhlman Personality Questionnaire-50- Cross-Cultural (ZKPQ-50-CC). The results were obtained with a sample of 928 volunteer subjects from the general population aged between 17 and 28 years old. Frequency distributions and alpha reliabilities with the three instruments were acceptable. Correlational and factorial analyses showed that several scales in the three instruments share an appreciable amount of common variance. Five factors emerged from principal components analysis. The first factor was integrated by A (Agreeableness), Co (Cooperativeness) and Agg-Host (Aggressiveness-Hostility), with secondary loadings in C (Conscientiousness) and SD (Self-directiveness) from other factors. The second factor was composed by N (Neuroticism), N-Anx (Neuroticism-Anxiety), HA (Harm Avoidance) and SD (Self-directiveness). The third factor was integrated by Sy (Sociability), E (Extraversion), RD (Reward Dependence), ImpSS (Impulsive Sensation Seeking) and NS (novelty Seeking). The fourth factor was integrated by Ps (Persistence), Act (Activity), and C, whereas the fifth and last factor was composed by O (Openness) and ST (Self- Transcendence). Confirmatory factor analyses indicate that the scales in each model are highly interrelated and define the specified latent dimension well. Similarities and differences between these three instruments are further discussed.
Resumo:
En el presente trabajo se presenta una revisión sobre los modelos forestales desarrollados en España durante los últimos años, tanto para la producción maderable como no maderable y, para la dinámica de los bosques (regeneración, mortalidad). Se presentan modelos tanto de rodal completo como de clases diamétricas y de árbol individual. Los modelos desarrollados hasta la fecha se han desarrollado a partir de datos procedentes de parcelas permanentes, ensayos y el Inventario Forestal Nacional. En el trabajo se muestran los diferentes submodelos desarrollados hasta la fecha, así como las plataformas informáticas que permiten utilizar dichos modelos. Se incluyen las principales perspectivas de desarrollo de la modelización forestal en España.
Resumo:
Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Resumo:
This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.
Resumo:
Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.
Resumo:
El bosc mediterrani ens proporciona una gran quantita de productes i serveis que poden contribuir a la riquesa i el benestar de la societat. La combinació dels diferents productes i serveis a través de models de gestió forestal multiobjectiu, com és el cas de la producció de fusta i bolets, permet avançar cap a la millora del potencial productiu del bosc i la preservació de les masses forestals.
Resumo:
We study general models of holographic superconductivity parametrized by four arbitrary functions of a neutral scalar field of the bulk theory. The models can accommodate several features of real superconductors, like arbitrary critical temperatures and critical exponents in a certain range, and perhaps impurities or boundary or thickness effects. We find analytical expressions for the critical exponents of the general model and show that they satisfy the Rushbrooke identity. An important subclass of models exhibit second order phase transitions. A study of the specific heat shows that general models can also describe holographic superconductors undergoing first, second and third (or higher) order phase transitions. We discuss how small deformations of the HHH model can lead to the appearance of resonance peaks in the conductivity, which increase in number and become narrower as the temperature is gradually decreased, without the need for tuning mass of the scalar to be close to the Breitenlohner-Freedman bound. Finally, we investigate the inclusion of a generalized ¿theta term¿ producing Hall effect without magnetic field.
Resumo:
The most general black M5-brane solution of eleven-dimensional supergravity (with a flat R4 spacetime in the brane and a regular horizon) is characterized by charge, mass and two angular momenta. We use this metric to construct general dual models of large-N QCD (at strong coupling) that depend on two free parameters. The mass spectrum of scalar particles is determined analytically (in the WKB approximation) and numerically in the whole two-dimensional parameter space. We compare the mass spectrum with analogous results from lattice calculations, and find that the supergravity predictions are close to the lattice results everywhere on the two dimensional parameter space except along a special line. We also examine the mass spectrum of the supergravity Kaluza-Klein (KK) modes and find that the KK modes along the compact D-brane coordinate decouple from the spectrum for large angular momenta. There are however KK modes charged under a U(1)×U(1) global symmetry which do not decouple anywhere on the parameter space. General formulas for the string tension and action are also given.
Resumo:
A one-parameter class of simple models of two-dimensional dilaton gravity, which can be exactly solved including back-reaction effects, is investigated at both classical and quantum levels. This family contains the RST model as a special case, and it continuously interpolates between models having a flat (Rindler) geometry and a constant curvature metric with a nontrivial dilaton field. The processes of formation of black hole singularities from collapsing matter and Hawking evaporation are considered in detail. Various physical aspects of these geometries are discussed, including the cosmological interpretation.
Resumo:
Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis and synthesis of the literature from managerial accounting, organizational theory, strategic management and social scientific causal modelling. Findings: The analysis indicates that dynamic, complex and uncertain environments may challenge any reliance upon valid causal models. Due to cognitive limitations and judgmental biases, managers may fail to trace correct cause-and-effect understanding of the value creation in their organizations. However, even lacking this validity, causal models can support strategic learning and perform as organizational guides if they are able to mobilize managerial action. Research limitations/implications: Future research should highlight the characteristics necessary for elaboration of convincing and appealing causal models and the social process of their construction. Practical implications: Managers of organizations using causal models should be clear on the purposes of their particular models and their limitations. In particular, difficulties are observed in specifying detailed cause and effect relations and their potential for communicating and directing attention. They should therefore construct their models to suit the particular purpose envisaged. Originality/value: This paper provides an interdisciplinary and holistic view on the issue of causality in managerial accounting models.
Resumo:
Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.
Resumo:
L"últim mes de maig, al IV Simposi de Filologia Valenciana -en honor de Joan Veny- organitzat pel Departament de Filologia Catalana de la Universitat de València, vaig exposar oralment la meua part en l"homenatge al mestre de Campos. Ecologia i caracterització dels parlars xurros fou el títol que els organitzadors em van proposar, el mateix que vaig servar per a la versió escrita destinada a les actes corresponents. Un parell de mesos després vaig rebre de l"amic Josep Martines l"encàrrec de col·laborar en el present número monogràfic sobre les relacions entre l"aragonès i el català. Encara en premsa aquella contribució sobre aspectes generals dels parlars castellanoaragonesos de l"interior valencià, n"ofereixo ara (desembre de 2000) una altra que pretén desenvolupar algunes qüestions particulars d"aquest món lingüístic de frontera.