CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

Ground cover and leaf area index relationship in a grass, legume and crucifer crop

Canopy characterization is essential for describing the interaction of a crop with its environment. The goal of this work was to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop, and to assess the feasibility of using these relationships as well as LAI-2000 readings to estimate LAI. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. Linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI mayor que 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley.

Thermal food processing optimization: Algorithms and software

The algorithms and graphic user interface software package ?OPT-PROx? are developed to meet food engineering needs related to canned food thermal processing simulation and optimization. The adaptive random search algorithm and its modification coupled with penalty function?s approach, and the finite difference methods with cubic spline approximation are utilized by ?OPT-PROx? package (http://tomakechoice. com/optprox/index.html). The diversity of thermal food processing optimization problems with different objectives and required constraints are solvable by developed software. The geometries supported by the ?OPT-PROx? are the following: (1) cylinder, (2) rectangle, (3) sphere. The mean square error minimization principle is utilized in order to estimate the heat transfer coefficient of food to be heated under optimal condition. The developed user friendly dialogue and used numerical procedures makes the ?OPT-PROx? software useful to food scientists in research and education, as well as to engineers involved in optimization of thermal food processing.

ANN and Fuzzy c-Means applied to environmental pollution prediction

Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.

Distributed target tracking based on belief propagation consensus

Distributed target tracking in wireless sensor networks (WSN) is an important problem, in which agreement on the target state can be achieved using conventional consensus methods, which take long to converge. We propose distributed particle filtering based on belief propagation (DPF-BP) consensus, a fast method for target tracking. According to our simulations, DPF-BP provides better performance than DPF based on standard belief consensus (DPF-SBC) in terms of disagreement in the network. However, in terms of root-mean square error, it can outperform DPF-SBC only for a specific number of consensus iterations.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Evaluation and improvement of empirical models of global solar irradiation: Case study northern Spain

This paper presents a new methodology to build parametric models to estimate global solar irradiation adjusted to specific on-site characteristics based on the evaluation of variable im- portance. Thus, those variables higly correlated to solar irradiation on a site are implemented in the model and therefore, different models might be proposed under different climates. This methodology is applied in a study case in La Rioja region (northern Spain). A new model is proposed and evaluated on stability and accuracy against a review of twenty-two already exist- ing parametric models based on temperatures and rainfall in seventeen meteorological stations in La Rioja. The methodology of model evaluation is based on bootstrapping, which leads to achieve a high level of confidence in model calibration and validation from short time series (in this case five years, from 2007 to 2011). The model proposed improves the estimates of the other twenty-two models with average mean absolute error (MAE) of 2.195 MJ/m2 day and average confidence interval width (95% C.I., n=100) of 0.261 MJ/m2 day. 41.65% of the daily residuals in the case of SIAR and 20.12% in that of SOS Rioja fall within the uncertainty tolerance of the pyranometers of the two networks (10% and 5%, respectively). Relative differences between measured and estimated irradiation on an annual cumulative basis are below 4.82%. Thus, the proposed model might be useful to estimate annual sums of global solar irradiation, reaching insignificant differences between measurements from pyranometers.

Tree height integrated into pantropical forest biomass estimates

Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- andWeibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (?40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8Mgha?1 (range 6.6 to 112.4) to 8.0Mgha?1 (?2.5 to 23.0). For all plots, aboveground live biomass was ?52.2 Mgha?1 (?82.0 to ?20.3 bootstrapped 95%CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in eastcentral Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 PgC (31?39 bootstrapped 95%CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Downscaling of global solar irradiation in R

A methodology for downscaling solar irradiation from satellite-derived databases is described using R software. Different packages such as raster, parallel, solaR, gstat, sp and rasterVis are considered in this study for improving solar resource estimation in areas with complex topography, in which downscaling is a very useful tool for reducing inherent deviations in satellite-derived irradiation databases, which lack of high global spatial resolution. A topographical analysis of horizon blocking and sky-view is developed with a digital elevation model to determine what fraction of hourly solar irradiation reaches the Earth's surface. Eventually, kriging with external drift is applied for a better estimation of solar irradiation throughout the region analyzed. This methodology has been implemented as an example within the region of La Rioja in northern Spain, and the mean absolute error found is a striking 25.5% lower than with the original database.

Carbon allocation in north-western Amazon forests (Colombia)

Los estudios sobre la asignación del carbono en los ecosistemas forestales proporcionan información esencial para la comprensión de las diferencias espaciales y temporales en el ciclo del carbono de tal forma que pueden aportar información a los modelos y, así predecir las posibles respuestas de los bosques a los cambios en el clima. Dentro de este contexto, los bosques Amazónicos desempeñan un papel particularmente importante en el balance global del carbono; no obstante, existen grandes incertidumbres en cuanto a los controles abióticos en las tasas de la producción primaria neta (PPN), la asignación de los productos de la fotosíntesis a los diferentes componentes o compartimentos del ecosistema (aéreo y subterráneo) y, cómo estos componentes de la asignación del carbono responden a eventos climáticos extremos. El objetivo general de esta tesis es analizar los componentes de la asignación del carbono en bosques tropicales maduros sobre suelos contrastantes, que crecen bajo condiciones climáticas similares en dos sitios ubicados en la Amazonia noroccidental (Colombia): el Parque Natural Nacional Amacayacu y la Estación Biológica Zafire. Con este objetivo, realicé mediciones de los componentes de la asignación del carbono (biomasa, productividad primaria neta, y su fraccionamiento) a nivel ecosistémico y de la dinámica forestal (tasas anuales de mortalidad y reclutamiento), a lo largo de ocho años (20042012) en seis parcelas permanentes de 1 hectárea establecidas en cinco tipos de bosques sobre suelos diferentes (arcilloso, franco-arcilloso, franco-arcilloso-arenoso, franco-arenoso y arena-francosa). Toda esta información me permitió abordar preguntas específicas que detallo a continuación. En el Capítulo 2 evalúe la hipótesis de que a medida que aumenta la fertilidad del suelo disminuye la cantidad del carbono asignado a la producción subterránea (raíces finas con diámetro <2 mm). Y para esto, realicé mediciones de la masa y la producción de raíces finas usando dos métodos: (1) el de los cilindros de crecimiento y, (2) el de los cilindros de extracción secuencial. El monitoreo se realizó durante 2.2 años en los bosques con suelos más contrastantes: arcilla y arena-francosa. Encontré diferencias significativas en la masa de raíces finas y su producción entre los bosques y, también con respecto a la profundidad del suelo (010 y 1020 cm). El bosque sobre arena-francosa asignó más carbono a las raíces finas que el bosque sobre arcillas. La producción de raíces finas en el bosque sobre arena-francosa fue dos veces más alta (media ± error estándar = 2.98 ± 0.36 y 3.33 ± 0.69 Mg C ha1 año1, con el método 1 y 2, respectivamente), que para el bosque sobre arcillas, el suelo más fértil (1.51 ± 0.14, método 1, y desde 1.03 ± 0.31 a 1.36 ± 0.23 Mg C ha1 año1, método 2). Del mismo modo, el promedio de la masa de raíces finas fue tres veces mayor en el bosque sobre arena-francosa (5.47 ± 0.17 Mg C ha1) que en el suelo más fértil (de 1.52 ± 0.08 a 1.82 ± 0.09 Mg C ha1). La masa de las raíces finas también mostró un patrón temporal relacionado con la lluvia, mostrando que la producción de raíces finas disminuyó sustancialmente en el período seco del año 2005. Estos resultados sugieren que los recursos del suelo pueden desempeñar un papel importante en los patrones de la asignación del carbono entre los componentes aéreo y subterráneo de los bosques tropicales; y que el suelo no sólo influye en las diferencias en la masa de raíces finas y su producción, sino que también, en conjunto con la lluvia, sobre la estacionalidad de la producción. En el Capítulo 3 estimé y analicé los tres componentes de la asignación del carbono a nivel del ecosistema: la biomasa, la productividad primaria neta PPN, y su fraccionamiento, en los mismos bosques del Capítulo 2 (el bosque sobre arcillas y el bosque sobre arena-francosa). Encontré diferencias significativas en los patrones de la asignación del carbono entre los bosques; el bosque sobre arcillas presentó una mayor biomasa total y aérea, así como una PPN, que el bosque sobre arena-francosa. Sin embargo, la diferencia entre los dos bosques en términos de la productividad primaria neta total fue menor en comparación con las diferencias entre la biomasa total de los bosques, como consecuencia de las diferentes estrategias en la asignación del carbono a los componentes aéreo y subterráneo del bosque. La proporción o fracción de la PPN asignada a la nueva producción de follaje fue relativamente similar entre los dos bosques. Nuestros resultados de los incrementos de la biomasa aérea sugieren una posible compensación entre la asignación del carbono al crecimiento de las raíces finas versus el de la madera, a diferencia de la compensación comúnmente asumida entre la parte aérea y la subterránea en general. A pesar de estas diferencias entre los bosques en términos de los componentes de la asignación del carbono, el índice de área foliar fue relativamente similar entre ellos, lo que sugiere que el índice de área foliar es más un indicador de la PPN total que de la asignación de carbono entre componentes. En el Capítulo 4 evalué la variación espacial y temporal de los componentes de la asignación del carbono y la dinámica forestal de cinco tipos e bosques amazónicos y sus respuestas a fluctuaciones en la precipitación, lo cual es completamente relevante en el ciclo global del carbono y los procesos biogeoquímicos en general. Estas variaciones son así mismo importantes para evaluar los efectos de la sequía o eventos extremos sobre la dinámica natural de los bosques amazónicos. Evalué la variación interanual y la estacionalidad de los componentes de la asignación del carbono y la dinámica forestal durante el periodo 2004−2012, en cinco bosques maduros sobre diferentes suelos (arcilloso, franco-arcilloso, franco-arcilloso-arenoso, franco-arenoso y arena-francosa), todos bajo el mismo régimen local de precipitación en la Amazonia noroccidental (Colombia). Quería examinar sí estos bosques responden de forma similar a las fluctuaciones en la precipitación, tal y como pronostican muchos modelos. Consideré las siguientes preguntas: (i) ¿Existe una correlación entre los componentes de la asignación del carbono y la dinámica forestal con la precipitación? (ii) ¿Existe correlación entre los bosques? (iii) ¿Es el índice de área foliar (LAI) un indicador de las variaciones en la producción aérea o es un reflejo de los cambios en los patrones de la asignación del carbono entre bosques?. En general, la correlación entre los componentes aéreo y subterráneo de la asignación del carbono con la precipitación sugiere que los suelos juegan un papel importante en las diferencias espaciales y temporales de las respuestas de estos bosques a las variaciones en la precipitación. Por un lado, la mayoría de los bosques mostraron que los componentes aéreos de la asignación del carbono son susceptibles a las fluctuaciones en la precipitación; sin embargo, el bosque sobre arena-francosa solamente presentó correlación con la lluvia con el componente subterráneo (raíces finas). Por otra parte, a pesar de que el noroeste Amazónico es considerado sin una estación seca propiamente (definida como <100 mm meses −1), la hojarasca y la masa de raíces finas mostraron una alta variabilidad y estacionalidad, especialmente marcada durante la sequía del 2005. Además, los bosques del grupo de suelos francos mostraron que la hojarasca responde a retrasos en la precipitación, al igual que la masa de raíces finas del bosque sobre arena-francosa. En cuanto a la dinámica forestal, sólo la tasa de mortalidad del bosque sobre arena-francosa estuvo correlacionada con la precipitación (ρ = 0.77, P <0.1). La variabilidad interanual en los incrementos en el tallo y la biomasa de los individuos resalta la importancia de la mortalidad en la variación de los incrementos en la biomasa aérea. Sin embargo, las tasas de mortalidad y las proporciones de individuos muertos por categoría de muerte (en pie, caído de raíz, partido y desaparecido), no mostraron tendencias claras relacionadas con la sequía. Curiosamente, la hojarasca, el incremento en la biomasa aérea y las tasas de reclutamiento mostraron una alta correlación entre los bosques, en particular dentro del grupo de los bosques con suelos francos. Sin embargo, el índice de área foliar estimado para los bosques con suelos más contrastantes (arcilla y arena-francosa), no presentó correlación significativa con la lluvia; no obstante, estuvo muy correlacionado entre bosques; índice de área foliar no reflejó las diferencias en la asignación de los componentes del carbono, y su respuesta a la precipitación en estos bosques. Por último, los bosques estudiados muestran que el noroeste amazónico es susceptible a fenómenos climáticos, contrario a lo propuesto anteriormente debido a la ausencia de una estación seca propiamente dicha. ABSTRACT Studies of carbon allocation in forests provide essential information for understanding spatial and temporal differences in carbon cycling that can inform models and predict possible responses to changes in climate. Amazon forests play a particularly significant role in the global carbon balance, but there are still large uncertainties regarding abiotic controls on the rates of net primary production (NPP) and the allocation of photosynthetic products to different ecosystem components; and how the carbon allocation components of Amazon forests respond to extreme climate events. The overall objective of this thesis is to examine the carbon allocation components in old-growth tropical forests on contrasting soils, and under similar climatic conditions in two sites at the Amacayacu National Natural Park and the Zafire Biological Station, located in the north-western Amazon (Colombia). Measurements of above- and below-ground carbon allocation components (biomass, net primary production, and its partitioning) at the ecosystem level, and dynamics of tree mortality and recruitment were done along eight years (20042012) in six 1-ha plots established in five Amazon forest types on different soils (clay, clay-loam, sandy-clay-loam, sandy-loam and loamy-sand) to address specific questions detailed in the next paragraphs. In Chapter 2, I evaluated the hypothesis that as soil fertility increases the amount of carbon allocated to below-ground production (fine-roots) should decrease. To address this hypothesis the standing crop mass and production of fine-roots (<2 mm) were estimated by two methods: (1) ingrowth cores and, (2) sequential soil coring, during 2.2 years in the most contrasting forests: the clay-soil forest and the loamy-sand forest. We found that the standing crop fine-root mass and its production were significantly different between forests and also between soil depths (0–10 and 10–20 cm). The loamysand forest allocated more carbon to fine-roots than the clay-soil forest, with fine-root production in the loamy-sand forest twice (mean ± standard error = 2.98 ± 0.36 and 3.33 ± 0.69 Mg C ha −1 yr −1, method 1 and 2, respectively) as much as for the more fertile claysoil forest (1.51 ± 0.14, method 1, and from 1.03 ± 0.31 to 1.36 ± 0.23 Mg C ha −1 yr −1, method 2). Similarly, the average of standing crop fine-root mass was three times higher in the loamy-sand forest (5.47 ± 0.17 Mg C ha1) than in the more fertile soil (from 1.52 ± 0.08 a 1.82 ± 0.09 Mg C ha1). The standing crop fine-root mass also showed a temporal pattern related to rainfall, with the production of fine-roots decreasing substantially in the dry period of the year 2005. These results suggest that soil resources may play an important role in patterns of carbon allocation of below-ground components, not only driven the differences in the biomass and its production, but also in the time when it is produced. In Chapter 3, I assessed the three components of stand-level carbon allocation (biomass, NPP, and its partitioning) for the same forests evaluated in Chapter 2 (clay-soil forest and loamy-sand forest). We found differences in carbon allocation patterns between these two forests, showing that the forest on clay-soil had a higher aboveground and total biomass as well as a higher above-ground NPP than the loamy-sand forest. However, differences between the two types of forests in terms of stand-level NPP were smaller, as a consequence of different strategies in the carbon allocation of above- and below-ground components. The proportional allocation of NPP to new foliage production was relatively similar between the two forests. Our results of aboveground biomass increments and fine-root production suggest a possible trade-off between carbon allocation to fine-roots versus wood growth (as it has been reported by other authors), as opposed to the most commonly assumed trade-off between total above- and below-ground production. Despite these differences among forests in terms of carbon allocation components, the leaf area index showed differences between forests like total NPP, suggesting that the leaf area index is more indicative of total NPP than carbon allocation. In Chapter 4, I evaluated the spatial and temporal variation of carbon allocation components and forest dynamics of Amazon forests as well as their responses to climatic fluctuations. I evaluated the intra- and inter-annual variation of carbon allocation components and forest dynamics during the period 2004−2012 in five forests on different soils (clay, clay-loam, sandy-clay-loam, sandy-loam and loamy-sand), but growing under the same local precipitation regime in north-western Amazonia (Colombia). We were interested in examining if these forests respond similarly to rainfall fluctuations as many models predict, considering the following questions: (i) Is there a correlation in carbon allocation components and forest dynamics with precipitation? (ii) Is there a correlation among forests? (iii) Are temporal responses in leaf area index (LAI) indicative of variations of above-ground production or a reflection of changes in carbon allocation patterns among forests?. Overall, the correlation of above- and below-ground carbon allocation components with rainfall suggests that soils play an important role in the spatial and temporal differences of responses of these forests to rainfall fluctuations. On the one hand, most forests showed that the above-ground components are susceptible to rainfall fluctuations; however, there was a forest on loamy-sand that only showed a correlation with the below-ground component (fine-roots). On the other hand, despite the fact that north-western Amazonia is considered without a conspicuous dry season (defined as <100 mm month−1), litterfall and fine-root mass showed high seasonality and variability, particularly marked during the drought of 2005. Additionally, forests of the loam-soil group showed that litterfall respond to time-lags in rainfall as well as and the fine-root mass of the loamy-sand forest. With regard to forest dynamics, only the mortality rate of the loamy-sand forest was significantly correlated with rainfall (77%). The observed inter-annual variability of stem and biomass increments of individuals highlighted the importance of the mortality in the above-ground biomass increment. However, mortality rates and death type proportion did not show clear trends related to droughts. Interestingly, litterfall, above-ground biomass increment and recruitment rates of forests showed high correlation among forests, particularly within the loam-soil forests group. Nonetheless, LAI measured in the most contrasting forests (clay-soil and loamysand) was poorly correlated with rainfall but highly correlated between forests; LAI did not reflect the differences in the carbon allocation components, and their response to rainfall on these forests. Finally, the forests studied highlight that north-western Amazon forests are also susceptible to climate fluctuations, contrary to what has been proposed previously due to their lack of a pronounced dry season.

Cooperative off-policy prediction of markov decision processes in adaptive networks

We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in large state spaces. We provide a mean-square-error performance analysis under constant step-sizes. The gain of cooperation in the form of more stability and less bias and variance in the prediction error, is illustrated in the context of a classical model. We show that the improvement in performance is especially significant when the behavior policy of the agents is different from the target policy under evaluation.

Evaluation of cover crops based on characteristics of nitrogen use, and aerial and root growth

La caracterización de los cultivos cubierta (cover crops) puede permitir comparar la idoneidad de diferentes especies para proporcionar servicios ecológicos como el control de la erosión, el reciclado de nutrientes o la producción de forrajes. En este trabajo se estudiaron bajo condiciones de campo diferentes técnicas para caracterizar el dosel vegetal con objeto de establecer una metodología para medir y comparar las arquitecturas de los cultivos cubierta más comunes. Se estableció un ensayo de campo en Madrid (España central) para determinar la relación entre el índice de área foliar (LAI) y la cobertura del suelo (GC) para un cultivo de gramínea, uno de leguminosa y uno de crucífera. Para ello se sembraron doce parcelas con cebada (Hordeum vulgare L.), veza (Vicia sativa L.), y colza (Brassica napus L.). En 10 fechas de muestreo se midieron el LAI (con estimaciones directas y del LAI-2000), la fracción interceptada de la radiación fotosintéticamente activa (FIPAR) y la GC. Un experimento de campo de dos años (Octubre-Abril) se estableció en la misma localización para evaluar diferentes especies (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) y cultivares (20) en relación con su idoneidad para ser usadas como cultivos cubierta. La GC se monitorizó mediante análisis de imágenes digitales con 21 y 22 muestreos, y la biomasa se midió 8 y 10 veces, respectivamente para cada año. Un modelo de Gompertz caracterizó la cobertura del suelo hasta el decaimiento observado tras las heladas, mientras que la biomasa se ajustó a ecuaciones de Gompertz, logísticas y lineales-exponenciales. Al final del experimento se determinaron el C, el N y el contenido en fibra (neutrodetergente, ácidodetergente y lignina), así como el N fijado por las leguminosas. Se aplicó el análisis de decisión multicriterio (MCDA) con objeto de obtener un ranking de especies y cultivares de acuerdo con su idoneidad para actuar como cultivos cubierta en cuatro modalidades diferentes: cultivo de cobertura, cultivo captura, abono verde y forraje. Las asociaciones de cultivos leguminosas con no leguminosas pueden afectar al crecimiento radicular y a la absorción de N de ambos componentes de la mezcla. El conocimiento de cómo los sistemas radiculares específicos afectan al crecimiento individual de las especies es útil para entender las interacciones en las asociaciones, así como para planificar estrategias de cultivos cubierta. En un tercer ensayo se combinaron estudios en rhizotrones con extracción de raíces e identificación de especies por microscopía, así como con estudios de crecimiento, absorción de N y 15N en capas profundas del suelo. Las interacciones entre raíces en su crecimiento y en el aprovisionamiento de N se estudiaron para dos de los cultivares mejor valorados en el estudio previo: uno de cebada (Hordeum vulgare L. cv. Hispanic) y otro de veza (Vicia sativa L. cv. Aitana). Se añadió N en dosis de 0 (N0), 50 (N1) y 150 (N2) kg N ha-1. Como resultados del primer estudio, se ajustaron correctamente modelos lineales y cuadráticos a la relación entre la GC y el LAI para todos los cultivos, pero en la gramínea alcanzaron una meseta para un LAI>4. Antes de alcanzar la cobertura total, la pendiente de la relación lineal entre ambas variables se situó en un rango entre 0.025 y 0.030. Las lecturas del LAI-2000 estuvieron correlacionadas linealmente con el LAI, aunque con tendencia a la sobreestimación. Las correcciones basadas en el efecto de aglutinación redujeron el error cuadrático medio del LAI estimado por el LAI-2000 desde 1.2 hasta 0.5 para la crucífera y la leguminosa, no siendo efectivas para la cebada. Esto determinó que para los siguientes estudios se midieran únicamente la GC y la biomasa. En el segundo experimento, las gramíneas alcanzaron la mayor cobertura del suelo (83-99%) y la mayor biomasa (1226-1928 g m-2) al final del mismo. Con la mayor relación C/N (27-39) y contenido en fibra digestible (53-60%) y la menor calidad de residuo (~68%). La mostaza presentó elevadas GC, biomasa y absorción de N en el año más templado en similitud con las gramíneas, aunque escasa calidad como forraje en ambos años. La veza presentó la menor absorción de N (2.4-0.7 g N m-2) debido a la fijación de N (9.8-1.6 g N m-2) y escasa acumulación de N. El tiempo térmico hasta alcanzar el 30% de GC constituyó un buen indicador de especies de rápida cubrición. La cuantificación de las variables permitió hallar variabilidad entre las especies y proporcionó información para posteriores decisiones sobre la selección y manejo de los cultivos cubierta. La agregación de dichas variables a través de funciones de utilidad permitió confeccionar rankings de especies y cultivares para cada uso. Las gramíneas fueron las más indicadas para los usos de cultivo de cobertura, cultivo captura y forraje, mientras que las vezas fueron las mejor como abono verde. La mostaza alcanzó altos valores como cultivo de cobertura y captura en el primer año, pero el segundo decayó debido a su pobre actuación en los inviernos fríos. Hispanic fue el mejor cultivar de cebada como cultivo de cobertura y captura, mientras que Albacete como forraje. El triticale Titania alcanzó la posición más alta como cultiva de cobertura, captura y forraje. Las vezas Aitana y BGE014897 mostraron buenas aptitudes como abono verde y cultivo captura. El MCDA permitió la comparación entre especies y cultivares proporcionando información relevante para la selección y manejo de cultivos cubierta. En el estudio en rhizotrones tanto la mezcla de especies como la cebada alcanzaron mayor intensidad de raíces (RI) y profundidad (RD) que la veza, con valores alrededor de 150 cruces m-1 y 1.4 m respectivamente, comparados con 50 cruces m-1 y 0.9 m para la veza. En las capas más profundas del suelo, la asociación de cultivos mostró valores de RI ligeramente mayores que la cebada en monocultivo. La cebada y la asociación obtuvieron mayores valores de densidad de raíces (RLD) (200-600 m m-3) que la veza (25-130) entre 0.8 y 1.2 m de profundidad. Los niveles de N no mostraron efectos claros en RI, RD ó RLD, sin embargo, el incremento de N favoreció la proliferación de raíces de veza en la asociación en capas profundas del suelo, con un ratio cebada/veza situado entre 25 a N0 y 5 a N2. La absorción de N de la cebada se incrementó en la asociación a expensas de la veza (de ~100 a 200 mg planta-1). Las raíces de cebada en la asociación absorbieron también más nitrógeno marcado de las capas profundas del suelo (0.6 mg 15N planta-1) que en el monocultivo (0.3 mg 15N planta-1). ABSTRACT Cover crop characterization may allow comparing the suitability of different species to provide ecological services such as erosion control, nutrient recycling or fodder production. Different techniques to characterize plant canopy were studied under field conditions in order to establish a methodology for measuring and comparing cover crops canopies. A field trial was established in Madrid (central Spain) to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. A two-year field experiment (October-April) was established in the same location to evaluate different species (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) and cultivars (20) according to their suitability to be used as cover crops. GC was monitored through digital image analysis with 21 and 22 samples, and biomass measured 8 and 10 times, respectively for each season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment C, N, and fiber (neutral detergent, acid and lignin) contents, and the N fixed by the legumes were determined. Multicriteria decision analysis (MCDA) was applied in order to rank the species and cultivars according to their suitability to perform as cover crops in four different modalities: cover crop, catch crop, green manure and fodder. Intercropping legumes and non-legumes may affect the root growth and N uptake of both components in the mixture. The knowledge of how specific root systems affect the growth of the individual species is useful for understanding the interactions in intercrops as well as for planning cover cropping strategies. In a third trial rhizotron studies were combined with root extraction and species identification by microscopy and with studies of growth, N uptake and 15N uptake from deeper soil layers. The root interactions of root growth and N foraging were studied for two of the best ranked cultivars in the previous study: a barley (Hordeum vulgare L. cv. Hispanic) and a vetch (Vicia sativa L. cv. Aitana). N was added at 0 (N0), 50 (N1) and 150 (N2) kg N ha-1. As a result, linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI > 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley. This determined that in the following studies only the GC and biomass were measured. In the second experiment, the grasses reached the highest ground cover (83- 99%) and biomass (1226-1928 g/m2) at the end of the experiment. The grasses had the highest C/N ratio (27-39) and dietary fiber (53-60%) and the lowest residue quality (~68%). The mustard presented high GC, biomass and N uptake in the warmer year with similarity to grasses, but low fodder capability in both years. The vetch presented the lowest N uptake (2.4-0.7 g N/m2) due to N fixation (9.8-1.6 g N/m2) and low biomass accumulation. The thermal time until reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crops selection and management. Aggregation of these variables through utility functions allowed ranking species and cultivars for each usage. Grasses were the most suitable for the cover crop, catch crop and fodder uses, while the vetches were the best as green manures. The mustard attained high ranks as cover and catch crop the first season, but the second decayed due to low performance in cold winters. Hispanic was the most suitable barley cultivar as cover and catch crop, and Albacete as fodder. The triticale Titania attained the highest rank as cover and catch crop and fodder. Vetches Aitana and BGE014897 showed good aptitudes as green manures and catch crops. MCDA allowed comparison among species and cultivars and might provide relevant information for cover crops selection and management. In the rhizotron study the intercrop and the barley attained slightly higher root intensity (RI) and root depth (RD) than the vetch, with values around 150 crosses m-1 and 1.4 m respectively, compared to 50 crosses m-1 and 0.9 m for the vetch. At deep soil layers, intercropping showed slightly larger RI values compared to the sole cropped barley. The barley and the intercropping had larger root length density (RLD) values (200-600 m m-3) than the vetch (25-130) at 0.8-1.2 m depth. The topsoil N supply did not show a clear effect on the RI, RD or RLD; however increasing topsoil N favored the proliferation of vetch roots in the intercropping at deep soil layers, with the barley/vetch root ratio ranging from 25 at N0 to 5 at N2. The N uptake of the barley was enhanced in the intercropping at the expense of the vetch (from ~100 mg plant-1 to 200). The intercropped barley roots took up more labeled nitrogen (0.6 mg 15N plant-1) than the sole-cropped barley roots (0.3 mg 15N plant-1) from deep layers.

A comparative analysis between FEM and Boundary Methods in bending of Plates

Two different methods of analysis of plate bending, FEM and BM are discussed in this paper. The plate behaviour is assumed to be represented by using the linear thin plate theory where the Poisson-Kirchoff assumption holds. The BM based in a weighted mean square error technique produced good results for the problem of plate bending. The computational effort demanded in the BM is smaller than the one needed in a FEM analysis for the same level of accuracy. The general application of the FEM cannot be matched by the BM. Particularly, different types of geometry (plates of arbitrary geometry) need a similar but not identical treatment in the BM. However, this loss of generality is counterbalanced by the computational efficiency gained in the BM in the solution achievement

Towards downscaling of aerosol gridded dataset for improving solar resource assessment, an application to Spain

Solar radiation estimates with clear sky models require estimations of aerosol data. The low spatial resolution of current aerosol datasets, with their remarkable drift from measured data, poses a problem in solar resource estimation. This paper proposes a new downscaling methodology by combining support vector machines for regression (SVR) and kriging with external drift, with data from the MACC reanalysis datasets and temperature and rainfall measurements from 213 meteorological stations in continental Spain. The SVR technique was proven efficient in aerosol variable modeling. The Linke turbidity factor (TL) and the aerosol optical depth at 550 nm (AOD 550) estimated with SVR generated significantly lower errors in AERONET positions than MACC reanalysis estimates. The TL was estimated with relative mean absolute error (rMAE) of 10.2% (compared with AERONET), against the MACC rMAE of 18.5%. A similar behavior was seen with AOD 550, estimated with rMAE of 8.6% (compared with AERONET), against the MACC rMAE of 65.6%. Kriging using MACC data as an external drift was found useful in generating high resolution maps (0.05° × 0.05°) of both aerosol variables. We created high resolution maps of aerosol variables in continental Spain for the year 2008. The proposed methodology was proven to be a valuable tool to create high resolution maps of aerosol variables (TL and AOD 550). This methodology shows meaningful improvements when compared with estimated available databases and therefore, leads to more accurate solar resource estimations. This methodology could also be applied to the prediction of other atmospheric variables, whose datasets are of low resolution.

An adaptive population importance sampler

Monte Carlo (MC) methods are widely used in signal processing, machine learning and communications for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we introduce an adaptive importance sampler using a population of proposal densities. The novel algorithm provides a global estimation of the variables of interest iteratively, using all the samples generated. The cloud of proposals is adapted by learning from a subset of previously generated samples, in such a way that local features of the target density can be better taken into account compared to single global adaptation procedures. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error and robustness to initialization.