Development of combined micro -preparation, separation, and mass spectrometry methods and application in the microdialysis study of neuropeptide metabolism

Two sets of mass spectrometry-based methods were developed specifically for the in vivo study of extracellular neuropeptide biochemistry. First, an integrated micro-concentration/desalting/matrix-addition device was constructed for matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) to achieve attomole sensitivity for microdialysis samples. Second, capillary electrophoresis (CE) was incorporated into the above micro-liquid chromatography (LC) and MALDI MS system to provide two-dimensional separation and identification (i.e. electrophoretic mobility and molecular mass) for the analysis of complex mixtures. The latter technique includes two parts of instrumentation: (1) the coupling of a preconcentration LC column to the inlet of a CE capillary, and (2) the utilization of a matrix-precoated membrane target for continuous CE effluent deposition and for automatic MALDI MS analysis (imaging) of the CE track.^ Initial in vivo data reveals a carboxypeptidase A (CPA) activity in rat brain involved in extracellular neurotensin metabolism. Benzylsuccinic acid, a CPA inhibitor, inhibited neurotensin metabolite NT1-12 formation by 70%, while inhibitors of other major extracellular peptide metabolizing enzymes increased NT1-12 formation. CPA activity has not been observed in previous in vitro experiments. Next, the validity of the methodology was demonstrated in the detection and structural elucidation of an endogenous neuropeptide, (L)VV-hemorphin-7, in rat brain upon ATP stimulation. Finally, the combined micro-LC/CE/MALDI MS was used in the in vivo metabolic study of peptide E, a mu-selective opioid peptide with 25 amino acid residues. Profiles of 88 metabolites were obtained, their identity being determined by their mass-to-charge ratio and electrophoretic mobility. The results indicate that there are several primary cleavage sites in vivo for peptide E in the release of its enkephalin-containing fragments. ^

Determinación de nitratos en vegetales : comparación de cuatro métodos analíticos

Para la cuantificación de nitratos hay numerosas técnicas y no existe entre los analistas unanimidad en la selección de la más adecuada. Por tal motivo, se compararon cuatro métodos para la determinación de nitratos en muestras vegetales con el fin de evaluar la correlación entre los mismos y establecer pautas para su utilización. Se utilizaron 690 muestras de lechuga (Lactuca sativa L. var. capitata), pertenecientes a los tipos arrepollado y mantecoso, recolectadas a lo largo de un año en el Mercado Cooperativo de Guaymallén (Mendoza, Argentina). Según los tenores de nitratos encontrados en la población estudiada se efectuó un sub-muestreo aleatorio estratificado proporcional para lograr un número de muestras que representaran la variabilidad del total de la población. Se utilizaron cuatro métodos para la determinación de nitratos: 1. destilación por arrastre con vapor, considerado como método de referencia 2. colorimetría por nitración con ácido salicílico 3. colorimetría modificada 4. potenciometría con electrodo selectivo Se probaron diferentes modelos de regresión entre el método de referencia y los otros tres, siendo el lineal el que mejor se ajustó en todos los casos. Los métodos estudiados tuvieron comportamiento semejante. La mayor correlación (r2 = 93 %) se observó entre la destilación por arrastre con vapor y la potenciometría; no obstante, los restantes también presentaron alta correlación. Consecuentemente, la elección del procedimiento analítico dependerá principalmente del número de muestras a analizar, del tiempo requerido por el análisis y del costo del mismo.

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Prokaryotic growth and presence of metabolic products and contamination tracers in rocks samples from ODP Leg 187 sites

The microbial population in samples of basalt drilled from the north of the Australian Antarctic Discordance (AAD) during Ocean Drilling Program Leg 187 were studied using deoxyribonucleic acid (DNA)-based methods and culturing techniques. The results showed the presence of a microbial population characteristic for the basalt environment. DNA sequence analysis revealed that microbes grouping within the Actinobacteria, green nonsulfur bacteria, the Cytophaga/Flavobacterium/Bacteroides (CFB) group, the Bacillus/Clostridium group, and the beta and gamma subclasses of the Proteobacteria were present in the basalt samples collected. The most dominant phylogenetic group, both in terms of the number of sequences retrieved and the intensities of the DNA bands obtained with the denaturing gradient gel electrophoresis analysis, was the gamma Proteobacteria. Enrichment cultures showed phylogenetic affiliation with the Actinobacteria, the CFB group, the Bacillus/Clostridium group, and the alpha, beta, gamma, and epsilon subclasses of the Proteobacteria. Comparison of native and enriched samples showed that few of the microbes found in native basalt samples grew in the enrichment cultures. Only seven clusters, two clusters within each of the CFB and Bacillus/Clostridium groups and five clusters within the gamma Proteobacteria, contained sequences from both native and enriched basalt samples with significant similarity. Results from cultivation experiments showed the presence of the physiological groups of iron reducers and methane producers. The presence of the iron/manganese-reducing bacterium Shewanella was confirmed with DNA analysis. The results indicate that iron reducers and lithotrophic methanogenic Archaea are indigenous to the ocean crust basalt and that the methanogenic Archaea may be important primary producers in this basaltic environment.

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance.

Particle methods parallel implementations by GP-GPU strategies

This paper outlines the problems found in the parallelization of SPH (Smoothed Particle Hydrodynamics) algorithms using Graphics Processing Units. Different results of some parallel GPU implementations in terms of the speed-up and the scalability compared to the CPU sequential codes are shown. The most problematic stage in the GPU-SPH algorithms is the one responsible for locating neighboring particles and building the vectors where this information is stored, since these specific algorithms raise many dificulties for a data-level parallelization. Because of the fact that the neighbor location using linked lists does not show enough data-level parallelism, two new approaches have been pro- posed to minimize bank conflicts in the writing and subsequent reading of the neighbor lists. The first strategy proposes an efficient coordination between CPU-GPU, using GPU algorithms for those stages that allow a straight forward parallelization, and sequential CPU algorithms for those instructions that involve some kind of vector reduction. This coordination provides a relatively orderly reading of the neighbor lists in the interactions stage, achieving a speed-up factor of x47 in this stage. However, since the construction of the neighbor lists is quite expensive, it is achieved an overall speed-up of x41. The second strategy seeks to maximize the use of the GPU in the neighbor's location process by executing a specific vector sorting algorithm that allows some data-level parallelism. Al- though this strategy has succeeded in improving the speed-up on the stage of neighboring location, the global speed-up on the interactions stage falls, due to inefficient reading of the neighbor vectors. Some changes to these strategies are proposed, aimed at maximizing the computational load of the GPU and using the GPU texture-units, in order to reach the maximum speed-up for such codes. Different practical applications have been added to the mentioned GPU codes. First, the classical dam-break problem is studied. Second, the wave impact of the sloshing fluid contained in LNG vessel tanks is also simulated as a practical example of particle methods

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

Inverse kinematics of a 6 DoF human upper limb using ANFIS and ANN for anticipatory actuation in ADL-based physical Neurorehabilitation

Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-based and an ANFIS-based solution to the inverse kinematics problem are evaluated. Materials and methods: Both the multilayer perceptron-based and the ANFIS-based inverse kinematics methods have been trained with three-dimensional Cartesian positions corresponding to the end-effector of healthy human upper limbs that execute two different activities of the daily life: "serving water from a jar" and "picking up a bottle". Validation of the proposed methodologies has been performed by a 10 fold cross-validation procedure. Results: Once trained, the systems are able to map 3D positions of the end-effector to the corresponding healthy biomechanical configurations. A high mean correlation coefficient and a low root mean squared error have been found for both the multilayer perceptron and ANFIS-based methods. Conclusions: The obtained results indicate that both systems effectively solve the inverse kinematics problem, but, due to its low computational load, crucial in real-time applications, along with its high performance, a multilayer perceptron-based solution, consisting in 3 input neurons, 1 hidden layer with 3 neurons and 6 output neurons has been considered the most appropriated for the target application.

Shaking table tests of structures with hysteretic dampers: experimental results vs. prediction using non-linear static methods

The use of seismic hysteretic dampers for passive control is increasing exponentially in recent years for both new and existing buildings. In order to utilize hysteretic dampers within a structural system, it is of paramount importance to have simplified design procedures based upon knowledge gained from theoretical studies and validated with experimental results. Non-linear Static Procedures (NSPs) are presented as an alternative to the force-based methods more common nowadays. The application of NSPs to conventional structures has been well established; yet there is a lack of experimental information on how NSPs apply to systems with hysteretic dampers. In this research, several shaking table tests were conducted on two single bay and single story 1:2 scale structures with and without hysteretic dampers. The maximum response of the structure with dampers in terms of lateral displacement and base shear obtained from the tests was compared with the prediction provided by three well-known NSPs: (1) the improved version of the Capacity Spectrum Method (CSM) from FEMA 440; (2) the improved version of the Displacement Coefficient Method (DCM) from FEMA 440; and (3) the N2 Method implemented in Eurocode 8. In general, the improved version of the DCM and N2 methods are found to provide acceptable accuracy in prediction, but the CSM tends to underestimate the response.

A Hierarchical Tracking Strategy for Vision-Based Applications On-Board UAVs

In this paper, we apply a hierarchical tracking strategy of planar objects (or that can be assumed to be planar) that is based on direct methods for vision-based applications on-board UAVs. The use of this tracking strategy allows to achieve the tasks at real-time frame rates and to overcome problems posed by the challenging conditions of the tasks: e.g. constant vibrations, fast 3D changes, or limited capacity on-board. The vast majority of approaches make use of feature-based methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations in which part of the object to track is outside of the field of view of the camera. The performance of the proposed tracking strategy on-board UAVs is evaluated with images from realflight tests using manually-generated ground truth information, accurate position estimation using a Vicon system, and also with simulated data from a simulation environment. Results show that the hierarchical tracking strategy performs better than wellknown feature-based algorithms and well-known configurations of direct methods, and that its performance is robust enough for vision-in-the-loop tasks, e.g. for vision-based landing tasks.

Analysis of the discharge capacity of radial-gated spillways using CFD and ANN - Oliana Dam case study.

The paper focuses on the analysis of radial-gated spillways, which is carried out by the solution of a numerical model based on the finite element method (FEM). The Oliana Dam is considered as a case study and the discharge capacity is predicted both by the application of a level-set-based free-surface solver and by the use of traditional empirical formulations. The results of the analysis are then used for training an artificial neural network to allow real-time predictions of the discharge in any situation of energy head and gate opening within the operation range of the reservoir. The comparison of the results obtained with the different methods shows that numerical models such as the FEM can be useful as a predictive tool for the analysis of the hydraulic performance of radial-gated spillways.

Towards an abstract domain for resource analysis of logic programs using sized types

We present a novel general resource analysis for logic programs based on sized types.Sized types are representations that incorporate structural (shape) information and allow expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. They also allow relating the sizes of terms and subterms occurring at different argument positions in logic predicates. Using these sized types, the resource analysis can infer both lower and upper bounds on the resources used by all the procedures in a program as functions on input term (and subterm) sizes, overcoming limitations of existing analyses and enhancing their precision. Our new resource analysis has been developed within the abstract interpretation framework, as an extension of the sized types abstract domain, and has been integrated into the Ciao preprocessor, CiaoPP. The abstract domain operations are integrated with the setting up and solving of recurrence equations for both, inferring size and resource usage functions. We show that the analysis is an improvement over the previous resource analysis present in CiaoPP and compares well in power to state of the art systems.

Vibro-acoustic analysis of spacecraft structures with thin air layers

Esta Tesis presenta un estudio sobre el comportamiento vibroacústico de estructuras espaciales que incluyen capas de aire delgadas, así como sobre su modelización numérica. Las capas de aire pueden constituir un elemento fundamental en estos sistemas, como paneles solares plegados, que se consideran el caso de estudio en este trabajo. Para evaluar la influencia de las capas de aire en la respuesta dinámica del sistema se presenta el uso de modelos unidimensionales. La modelización de estos sistemas se estudia para los rangos de baja y alta frecuencia. En el rango de baja frecuencia se propone un conjunto de estrategias de simulación basadas en técnicas numéricas que se utilizan habitualmente en la industria aeroespacial para facilitar la aplicación de los resultados de la Tesis en los modelos numéricos actuales. Los resultados muestran el importante papel de las capas de aire en la respuesta del sistema. El uso de modelos basados en elementos finitos o de contorno para estos elementos proporciona resultados equivalentes aunque la aplicabilidad de estos últimos puede estar condicionada por la geometría del problema. Se estudia asimismo el uso del Análisis Estadístico de la Energía (SEA) para estos elementos. Una de las estrategias de simulación propuestas, que incluye una formulación energética para el aire que rodea a la estructura, se propone como estimador preliminar de la respuesta del sistema y sus frecuencias propias. Para el rango de alta frecuencia, se estudia la influencia de la definición del propio modelo SEA. Se presenta el uso de técnicas de reducción para determinar una matriz de pérdidas SEA reducida para definiciones incompletas del sistema (si algún elemento que interactúa con el resto no se incluye en el modelo). Esta nueva matriz tiene en cuenta la contribución de las subestructuras que no se consideran parte del modelo y que suelen ignorarse en el procedimiento habitual para reducir el tamaño del mismo. Esta matriz permite también analizar sistemas que incluyen algún componente con problemas de accesibilidad para medir su respuesta. Respecto a la determinación de los factores de pérdidas del sistema, se presenta una metodología que permite abordar casos en los que el método usual, el Método de Inyección de Potencia (PIM), no puede usarse. Se presenta un conjunto de métodos basados en la técnicas de optimización y de actualización de modelos para casos en los que no se puede medir la respuesta de todos los elementos del sistema y también para casos en los que no todos los elementos pueden ser excitados, abarcando un conjunto de casos más amplio que el abordable con el PIM. Para ambos rangos de frecuencia se presentan diferentes casos de análisis: modelos numéricos para validar los métodos propuestos y un panel solar plegado como caso experimental que pone de manifiesto la aplicación práctica de los métodos presentados en la Tesis. ABSTRACT This Thesis presents an study on the vibro-acoustic behaviour of spacecraft structures with thin air layers and their numerical modelling. The air layers can play a key role in these systems as solar wings in folded configuration that constitute the study case for this Thesis. A method based on one-dimensional models is presented to assess the influence of the air layers in the dynamic response of the system. The modelling of such systems is studied for low and high frequency ranges. In the low frequency range a set of modelling strategies are proposed based on numerical techniques used in the industry to facilitate the application of the results in the current numerical models. Results show the active role of the air layers in the system response and their great level of influence. The modelling of these elements by means of Finite Elements (FE) and Boundary Elements (BE) provide equivalent results although the applicability of BE models can be conditioned by the geometry of the problem. The use of Statistical Energy Analysis (SEA) for these systems is also presented. Good results on the system response are found for models involving SEA beyond the usual applicability limit. A simulation strategy, involving energetic formulation for the surrounding fluid is proposed as fast preliminary approach for the system response and the coupled eigenfrequencies. For the high frequency range, the influence of the definition of the SEA model is presented. Reduction techniques are used to determine a Reduced SEA Loss Matrix if the system definition is not complete and some elements, which interact with the rest, are not included. This new matrix takes into account the contribution of the subsystems not considered that are neglected in the usual approach for decreasing the size of the model. It also allows the analysis of systems with accessibility restrictions on some element in order to measure its response. Regarding the determination of the loss factors of a system, a methodology is presented for cases in which the usual Power Injection Method (PIM) can not be applied. A set of methods are presented for cases in which not all the subsystem responses can be measured or not all the subsystems can be excited, as solar wings in folded configuration. These methods, based on error minimising and model updating techniques can be used to calculate the system loss factors in a set of cases wider than the PIM’s. For both frequency ranges, different test problems are analysed: Numerical models are studied to validate the methods proposed; an experimental case consisting in an actual solar wing is studied on both frequency ranges to highlight the industrial application of the new methods presented in the Thesis.

Contribuciones al análisis de problemas supercomplejos de toma de decisiones

Los fundamentos de la Teoría de la Decisión Bayesiana proporcionan un marco coherente en el que se pueden resolver los problemas de toma de decisiones. La creciente disponibilidad de ordenadores potentes está llevando a tratar problemas cada vez más complejos con numerosas fuentes de incertidumbre multidimensionales; varios objetivos conflictivos; preferencias, metas y creencias cambiantes en el tiempo y distintos grupos afectados por las decisiones. Estos factores, a su vez, exigen mejores herramientas de representación de problemas; imponen fuertes restricciones cognitivas sobre los decisores y conllevan difíciles problemas computacionales. Esta tesis tratará estos tres aspectos. En el Capítulo 1, proporcionamos una revisión crítica de los principales métodos gráficos de representación y resolución de problemas, concluyendo con algunas recomendaciones fundamentales y generalizaciones. Nuestro segundo comentario nos lleva a estudiar tales métodos cuando sólo disponemos de información parcial sobre las preferencias y creencias del decisor. En el Capítulo 2, estudiamos este problema cuando empleamos diagramas de influencia (DI). Damos un algoritmo para calcular las soluciones no dominadas en un DI y analizamos varios conceptos de solución ad hoc. El último aspecto se estudia en los Capítulos 3 y 4. Motivado por una aplicación de gestión de embalses, introducimos un método heurístico para resolver problemas de decisión secuenciales. Como muestra resultados muy buenos, extendemos la idea a problemas secuenciales generales y cuantificamos su bondad. Exploramos después en varias direcciones la aplicación de métodos de simulación al Análisis de Decisiones. Introducimos primero métodos de Monte Cario para aproximar el conjunto no dominado en problemas continuos. Después, proporcionamos un método de Monte Cario basado en cadenas de Markov para problemas con información completa con estructura general: las decisiones y las variables aleatorias pueden ser continuas, y la función de utilidad puede ser arbitraria. Nuestro esquema es aplicable a muchos problemas modelizados como DI. Finalizamos con un capítulo de conclusiones y problemas abiertos.---ABSTRACT---The foundations of Bayesian Decisión Theory provide a coherent framework in which decisión making problems may be solved. With the advent of powerful computers and given the many challenging problems we face, we are gradually attempting to solve more and more complex decisión making problems with high and multidimensional uncertainty, múltiple objectives, influence of time over decisión tasks and influence over many groups. These complexity factors demand better representation tools for decisión making problems; place strong cognitive demands on the decison maker judgements; and lead to involved computational problems. This thesis will deal with these three topics. In recent years, many representation tools have been developed for decisión making problems. In Chapter 1, we provide a critical review of most of them and conclude with recommendations and generalisations. Given our second query, we could wonder how may we deal with those representation tools when there is only partial information. In Chapter 2, we find out how to deal with such a problem when it is structured as an influence diagram (ID). We give an algorithm to compute nondominated solutions in ID's and analyse several ad hoc solution concepts.- The last issue is studied in Chapters 3 and 4. In a reservoir management case study, we have introduced a heuristic method for solving sequential decisión making problems. Since it shows very good performance, we extend the idea to general problems and quantify its goodness. We explore then in several directions the application of simulation based methods to Decisión Analysis. We first introduce Monte Cario methods to approximate the nondominated set in continuous problems. Then, we provide a Monte Cario Markov Chain method for problems under total information with general structure: decisions and random variables may be continuous, and the utility function may be arbitrary. Our scheme is applicable to many problems modeled as IDs. We conclude with discussions and several open problems.

Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades

The aim of this work is to develop an automated tool for the optimization of turbomachinery blades founded on an evolutionary strategy. This optimization scheme will serve to deal with supersonic blades cascades for application to Organic Rankine Cycle (ORC) turbines. The blade geometry is defined using parameterization techniques based on B-Splines curves, that allow to have a local control of the shape. The location in space of the control points of the B-Spline curve define the design variables of the optimization problem. In the present work, the performance of the blade shape is assessed by means of fully-turbulent flow simulations performed with a CFD package, in which a look-up table method is applied to ensure an accurate thermodynamic treatment. The solver is set along with the optimization tool to determine the optimal shape of the blade. As only blade-to-blade effects are of interest in this study, quasi-3D calculations are performed, and a single-objective evolutionary strategy is applied to the optimization. As a result, a non-intrusive tool, with no need for gradients definition, is developed. The computational cost is reduced by the use of surrogate models. A Gaussian interpolation scheme (Kriging model) is applied for the estimated n-dimensional function, and a surrogate-based local optimization strategy is proved to yield an accurate way for optimization. In particular, the present optimization scheme has been applied to the re-design of a supersonic stator cascade of an axial-flow turbine. In this design exercise very strong shock waves are generated in the rear blade suction side and shock-boundary layer interaction mechanisms occur. A significant efficiency improvement as a consequence of a more uniform flow at the blade outlet section of the stator is achieved. This is also expected to provide beneficial effects on the design of a subsequent downstream rotor. The method provides an improvement to gradient-based methods and an optimized blade geometry is easily achieved using the genetic algorithm.