Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

Semi-algebraic methods for symbolic analysis of complex reaction networks

The identification of chemical mechanism that can exhibit oscillatory phenomena in reaction networks are currently of intense interest. In particular, the parametric question of the existence of Hopf bifurcations has gained increasing popularity due to its relation to the oscillatory behavior around the fixed points. However, the detection of oscillations in high-dimensional systems and systems with constraints by the available symbolic methods has proven to be difficult. The development of new efficient methods are therefore required to tackle the complexity caused by the high-dimensionality and non-linearity of these systems. In this thesis, we mainly present efficient algorithmic methods to detect Hopf bifurcation fixed points in (bio)-chemical reaction networks with symbolic rate constants, thereby yielding information about their oscillatory behavior of the networks. The methods use the representations of the systems on convex coordinates that arise from stoichiometric network analysis. One of the methods called HoCoQ reduces the problem of determining the existence of Hopf bifurcation fixed points to a first-order formula over the ordered field of the reals that can then be solved using computational-logic packages. The second method called HoCaT uses ideas from tropical geometry to formulate a more efficient method that is incomplete in theory but worked very well for the attempted high-dimensional models involving more than 20 chemical species. The instability of reaction networks may lead to the oscillatory behaviour. Therefore, we investigate some criterions for their stability using convex coordinates and quantifier elimination techniques. We also study Muldowney's extension of the classical Bendixson-Dulac criterion for excluding periodic orbits to higher dimensions for polynomial vector fields and we discuss the use of simple conservation constraints and the use of parametric constraints for describing simple convex polytopes on which periodic orbits can be excluded by Muldowney's criteria. All developed algorithms have been integrated into a common software framework called PoCaB (platform to explore bio- chemical reaction networks by algebraic methods) allowing for automated computation workflows from the problem descriptions. PoCaB also contains a database for the algebraic entities computed from the models of chemical reaction networks.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts

Evaluation of the effectiveness of an organization in the field of brand perception using a computer agent-based simulation system

Este proyecto de investigación busca usar un sistema de cómputo basado en modelación por agentes para medir la percepción de marca de una organización en una población heterogénea. Se espera proporcionar información que permita dar soluciones a una organización acerca del comportamiento de sus consumidores y la asociada percepción de marca. El propósito de este sistema es el de modelar el proceso de percepción-razonamiento-acción para simular un proceso de razonamiento como el resultado de una acumulación de percepciones que resultan en las acciones del consumidor. Este resultado definirá la aceptación de marca o el rechazo del consumidor hacia la empresa. Se realizó un proceso de recolección información acerca de una organización específica en el campo de marketing. Después de compilar y procesar la información obtenida de la empresa, el análisis de la percepción de marca es aplicado mediante procesos de simulación. Los resultados del experimento son emitidos a la organización mediante un informe basado en conclusiones y recomendaciones a nivel de marketing para mejorar la percepción de marca por parte de los consumidores.

Analysis of psychological aspects of Lovemarks formation

El presente trabajo es una revisión de literatura que busca contribuir al entendimiento de los procesos psicológicos subyacentes en la Teoría de Roberts sobre Lovemarks que, dentro del campo del marketing, ha buscado reemplazar la idea que se tiene sobre las marcas. La primera parte proporciona una introducción de lo que ha sido la evolución de las marcas desde una perspectiva psicológica y de mercadeo. En la segunda parte se explica la teoría de Lovemarks haciendo énfasis en sus componentes: el eje amor/respeto, las características de misterio, sensualidad e intimidad. Adicionalmente, se soporta esta teoría a través de literatura complementaria y casos de aplicación exitosos. La tercera parte, corresponde a la identificación y análisis de los procesos y aspectos psicológicos que explican la formación de un Lovemark: percepción, memoria, motivación individual y social y emoción. La cuarta y última parte contiene las conclusiones e implicaciones en la formación de la relación entre el consumidor y una marca.

Performance indicators for the physical therapy program’s field academic programs at the Universidad del Rosario for 2004-2007.

Introducción: El programa de Fisioterapia de la Universidad del Rosario, en su responsabilidad social de generar un impacto positivo en la comunidad y en su propósito de formar profesionales, cuenta con los Programas Académicos de Campo (PAC) que se consideran una fuerte estrategia de extensión de la Universidad. Los PAC contribuyen a la adquisición de competencias para el desarrollo de procesos de acción-actuación-creación en los estudiantes para que resuelvan problemas en un espacio real de ejercicio profesional. Bajo esta perspectiva los PAC del programa de Fisioterapia muestran su comportamiento a través de la medición de indicadores de proceso y resultados propuestos desde el Programa con el fin de proveer información útil para la reorientación y permanente actualización de los contenidos programáticos en las asignaturas y en los mismos PAC. Materiales y métodos: En el siguiente artículo se presenta un análisis de los indicadores de demanda por género, régimen de Seguridad Social en Salud, procedimiento y morbilidad de los Programas Académicos de Campo Integral Pediátrico, Integral de Adultos y Rehabilitación cardíaca y/o pulmonar, con el fin de establecer las características de la población objeto de la prestación de los servicios y procurar información verificable que dé soporte para la construcción de procesos de cambio dentro de la dinámica de mejoramiento continuo que debe tener cualquier institución. Este seguimiento es útil para la toma de decisiones de planeación académica que contribuye a mejorar los procesos de planeación y a facilitar el cumplimiento de los propósitos de formación para cada práctica, y de esta manera ayuda a ser elemento de análisis para directivas, instructores y estudiantes en la orientación del proceso de gestión académico-administrativo, y a retroalimentar los procesos de planeación y programación académica. Resultados: Los resultados arrojados en el análisis de los datos de la morbilidad en los programas académicos de campo muestran el siguiente comportamiento durante los años 2004, 2005, 2006 y 2007. Conclusiones: En el PAC pediátrico la mayor incidencia es de asma con un 37,2% y la más baja incidencia es para luxación congénita de cadera y enfermedad mental de origen central con un 0,1%. El 58% de los usuarios es de género masculino, y el 81% del total pertenece al régimen contributivo. En la morbilidad del PAC de adultos la mayor incidencia es de EPOC, con un 23,2%, y la menor incidencia es de lumbalgia, con un 2,4%. La mayoría de usuarios atendidos (58%) son hombres, y el 58% de los usuarios pertenece al régimen contributivo. En el PAC de rehabilitación cardíaca y/o pulmonar la mayor incidencia fue de EPOC, con un 40%; seguido de neumonía, con 17%; y con una menor incidencia para asma, con un 2%. El 54% de los usuarios son hombres y el 91% del total pertenece al régimen subsidiado.

cultural field of the seventeenth century in Spain and New Granada

The article aims to make visible some nuances of the 17TH century in Spain and the New Granada with emphasis on articulations and tensions that made up this cultural and social space through the analysis of the letrados and its position in the Hispanic cultural field of the 16th and 17TH centuries. This article also discusses the traditional thesis about the cultural isolation and obscurantism in the American colonies before the eighteenth century through the analysis of the circulation of books and knowledge between mainland Spain and its colonies, and the heterogeneous character of the lawyers that affect the symbolic monopoly of the Catholic Church.

A calibrated, non-invasive method for measuring the internal interface height field at high resolution in the rotating, two-layer annulus

We describe a remote sensing method for measuring the internal interface height field in a rotating, two-layer annulus laboratory experiment. The method is non-invasive, avoiding the possibility of an interaction between the flow and the measurement device. The height fields retrieved are accurate and highly resolved in both space and time. The technique is based on a flow visualization method developed by previous workers, and relies upon the optical rotation properties of the working liquids. The previous methods returned only qualitative interface maps, however. In the present study, a technique is developed for deriving quantitative maps by calibrating height against the colour fields registered by a camera which views the flow from above. We use a layer-wise torque balance analysis to determine the equilibrium interface height field analytically, in order to derive the calibration curves. With the current system, viewing an annulus of outer radius 125 mm and depth 250 mm from a distance of 2 m, the inferred height fields have horizontal, vertical and temporal resolutions of up to 0.2 mm, 1 mm and 0.04 s, respectively.

Independent component analysis of climate data: A new look at EOF rotation

The complexity inherent in climate data makes it necessary to introduce more than one statistical tool to the researcher to gain insight into the climate system. Empirical orthogonal function (EOF) analysis is one of the most widely used methods to analyze weather/climate modes of variability and to reduce the dimensionality of the system. Simple structure rotation of EOFs can enhance interpretability of the obtained patterns but cannot provide anything more than temporal uncorrelatedness. In this paper, an alternative rotation method based on independent component analysis (ICA) is considered. The ICA is viewed here as a method of EOF rotation. Starting from an initial EOF solution rather than rotating the loadings toward simplicity, ICA seeks a rotation matrix that maximizes the independence between the components in the time domain. If the underlying climate signals have an independent forcing, one can expect to find loadings with interpretable patterns whose time coefficients have properties that go beyond simple noncorrelation observed in EOFs. The methodology is presented and an application to monthly means sea level pressure (SLP) field is discussed. Among the rotated (to independence) EOFs, the North Atlantic Oscillation (NAO) pattern, an Arctic Oscillation–like pattern, and a Scandinavian-like pattern have been identified. There is the suggestion that the NAO is an intrinsic mode of variability independent of the Pacific.

The analysis of ranked observations of soil structure using indicator geostatistics

Structure is an important physical feature of the soil that is associated with water movement, the soil atmosphere, microorganism activity and nutrient uptake. A soil without any obvious organisation of its components is known as apedal and this state can have marked effects on several soil processes. Accurate maps of topsoil and subsoil structure are desirable for a wide range of models that aim to predict erosion, solute transport, or flow of water through the soil. Also such maps would be useful to precision farmers when deciding how to apply nutrients and pesticides in a site-specific way, and to target subsoiling and soil structure stabilization procedures. Typically, soil structure is inferred from bulk density or penetrometer resistance measurements and more recently from soil resistivity and conductivity surveys. To measure the former is both time-consuming and costly, whereas observations made by the latter methods can be made automatically and swiftly using a vehicle-mounted penetrometer or resistivity and conductivity sensors. The results of each of these methods, however, are affected by other soil properties, in particular moisture content at the time of sampling, texture, and the presence of stones. Traditional methods of observing soil structure identify the type of ped and its degree of development. Methods of ranking such observations from good to poor for different soil textures have been developed. Indicator variograms can be computed for each category or rank of structure and these can be summed to give the sum of indicator variograms (SIV). Observations of the topsoil and subsoil structure were made at four field sites where the soil had developed on different parent materials. The observations were ranked by four methods and indicator and the sum of indicator variograms were computed and modelled for each method of ranking. The individual indicators were then kriged with the parameters of the appropriate indicator variogram model to map the probability of encountering soil with the structure represented by that indicator. The model parameters of the SIVs for each ranking system were used with the data to krige the soil structure classes, and the results are compared with those for the individual indicators. The relations between maps of soil structure and selected wavebands from aerial photographs are examined as basis for planning surveys of soil structure. (C) 2007 Elsevier B.V. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

The use of FT-IR as a screening technique for organic residue analysis of archaeological samples

A range of archaeological samples have been examined using FT-IR spectroscopy. These include suspected coprolite samples from the Neolithic site of Catalhoyuk in Turkey, pottery samples from the Roman site of Silchester, UK and the Bronze Age site of Gatas, Spain and unidentified black residues on pottery sherds from the Roman sites of Springhead and Cambourne, UK. For coprolite samples the aim of FT-IR analysis is identification. Identification of coprolites in the field is based on their distinct orange colour; however, such visual identifications can often be misleading due to their similarity with deposits such as ochre and clay. For pottery the aim is to screen those samples that might contain high levels of organic residues which would be suitable for GC-MS analysis. The experiments have shown coprolites to have distinctive spectra, containing strong peaks from calcite, phosphate and quartz; the presence of phosphorus may be confirmed by SEM-EDX analysis. Pottery containing organic residues of plant and animal origin has also been shown to generally display strong phosphate peaks. FT-IR has distinguished between organic resin and non-organic compositions for the black residues, with differences also being seen between organic samples that have the same physical appearance. Further analysis by CC-MS has confirmed the identification of the coprolites through the presence of coprostanol and bile acids, and shows that the majority of organic pottery residues are either fatty acids or mono- or di-acylglycerols from foodstuffs, or triterpenoid resin compounds exposed to high temperatures. One suspected resin sample was shown to contain no organic residues. and it is seen that resin samples with similar physical appearances have different chemical compositions. FT-IR is proposed as a quick and cheap method of screening archaeological samples before subjecting them to the more expensive and time-consuming method of GC-MS. This will eliminate inorganic samples such as clays and ochre from CC-MS analysis, and will screen those samples which are most likely to have a high concentration of preserved organic residues. (C) 2008 Elsevier B.V. All rights reserved.

Excess open solar magnetic flux from satellite data: 1. Analysis of the third perihelion Ulysses pass

We use the third perihelion pass by the Ulysses spacecraft to illustrate and investigate the “flux excess” effect, whereby open solar flux estimates from spacecraft increase with increasing heliocentric distance. We analyze the potential effects of small-scale structure in the heliospheric field (giving fluctuations in the radial component on timescales smaller than 1 h) and kinematic time-of-flight effects of longitudinal structure in the solar wind flow. We show that the flux excess is explained by neither very small-scale structure (timescales < 1 h) nor by the kinematic “bunching effect” on spacecraft sampling. The observed flux excesses is, however, well explained by the kinematic effect of larger-scale (>1 day) solar wind speed variations on the frozen-in heliospheric field. We show that averaging over an interval T (that is long enough to eliminate structure originating in the heliosphere yet small enough to avoid cancelling opposite polarity radial field that originates from genuine sector structure in the coronal source field) is only an approximately valid way of allowing for these effects and does not adequately explain or account for differences between the streamer belt and the polar coronal holes.