Estudio de la extracción química del fe en madera arqueológica subacuatica tratada previamente con peg 4000

Debido a la gran cantidad de muestras arqueológicas impregnadas con PEG que se encuentran contaminadas por compuestos insolubles de hierro, se plantea la posible extracción y formación de complejos Fe-L (L=PBTC) y sus efectos en (i) la estructura de la matriz orgánica, (ii) la estructura y propiedades físicas del PEG y (iii) el comportamiento de la muestra en la etapa posterior de almacenamiento. El proyecto analiza la formación de compuestos químicos y posibles modificaciones estructurales en el proceso de extracción del hierro. Consiste en un estudio sistemático de un sistema químico y su influencia en los procesos de precipitación de Fe3+ en medio acuoso. El proyecto se fundamenta en: (1) desarrollar un proceso experimental de optimización para la extracción de las sales contaminantes y (2) encontrar las técnicas analíticas óptimas que permitan apreciar modificaciones estructurales de los diferentes sistemas. Se determina la cantidad de hierro extraído mediante A.A. Las interacciones entre PBTC y PEG se analizan por IR. Las modificaciones de determinadas propiedades físicas se determinan por DSC y las estructurales mediante SEM. En las condiciones termodinámicas óptimas se obtiene una extracción superficial del hierro (30-35%). La disolución del PEG origina modificaciones de la masa y el volumen de la muestra

Counter-ion effect on surfactant-DNA gel particles as controlled DNA delivery systems

The ability to entrap drugs within vehicles and subsequently release them has led to new treatments for a number of diseases. Based on an associative phase separation and interfacial diffusion approach, we developed a way to prepare DNA gel particles without adding any kind of cross-linker or organic solvent. Among the various agents studied, cationic surfactants offered particularly efficient control for encapsulation and DNA release from these DNA gel particles. The driving force for this strong association is the electrostatic interaction between the two components, as induced by the entropic increase due to the release of the respective counter-ions. However, little is known about the influence of the respective counter-ions on this surfactant-DNA interaction. Here we examined the effect of different counter-ions on the formation and properties of the DNA gel particles by mixing DNA (either single- (ssDNA) or double-stranded (dsDNA)) with the single chain surfactant dodecyltrimethylammonium (DTA). In particular, we used as counter-ions of this surfactant the hydrogen sulfate and trifluoromethane sulfonate anions and the two halides, chloride and bromide. Effects on the morphology of the particles obtained, the encapsulation of DNA and its release, as well as the haemocompatibility of these particles, are presented, using the counter-ion structure and the DNA conformation as controlling parameters. Analysis of the data indicates that the degree of counter-ion dissociation from the surfactant micelles and the polar/hydrophobic character of the counter-ion are important parameters in the final properties of the particles. The stronger interaction with amphiphiles for ssDNA than for dsDNA suggests the important role of hydrophobic interactions in DNA.

Extent and limitations of density functional theory in describing magnetic systems

The performance of density-functional theory to solve the exact, nonrelativistic, many-electron problem for magnetic systems has been explored in a new implementation imposing space and spin symmetry constraints, as in ab initio wave function theory. Calculations on selected systems representative of organic diradicals, molecular magnets and antiferromagnetic solids carried out with and without these constraints lead to contradictory results, which provide numerical illustration on this usually obviated problem. It is concluded that the present exchange-correlation functionals provide reasonable numerical results although for the wrong physical reasons, thus evidencing the need for continued search for more accurate expressions.

Extent and limitations of density functional theory in describing magnetic systems

The performance of density-functional theory to solve the exact, nonrelativistic, many-electron problem for magnetic systems has been explored in a new implementation imposing space and spin symmetry constraints, as in ab initio wave function theory. Calculations on selected systems representative of organic diradicals, molecular magnets and antiferromagnetic solids carried out with and without these constraints lead to contradictory results, which provide numerical illustration on this usually obviated problem. It is concluded that the present exchange-correlation functionals provide reasonable numerical results although for the wrong physical reasons, thus evidencing the need for continued search for more accurate expressions.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Reliability of the density functional approximation to describe the charge transfer and electrostatic complexes involved in the modeling of organic conducting polymers

Both the intermolecular interaction energies and the geometries for M ̄ thiophene, M ̄ pyrrole, M n+ ̄ thiophene, and M n+ ̄ pyrrole ͑with M = Li, Na, K, Ca, and Mg; and M n+ = Li+ , Na+ , K+ , Ca2+, and Mg2+͒ have been estimated using four commonly used density functional theory ͑DFT͒ methods: B3LYP, B3PW91, PBE, and MPW1PW91. Results have been compared to those provided by HF, MP2, and MP4 conventional ab initio methods. The PBE and MPW1PW91 are the only DFT methods able to provide a reasonable description of the M ̄ complexes. Regarding M n+ ̄ ␲ complexes, the four DFT methods have been proven to be adequate in the prediction of these electrostatically stabilized systems, even though they tend to overestimate the interaction energies.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Fertilizing Methods and Nutrient Balance at the End of Traditional Organic Agriculture in the Mediterranean Bioregion: Catalonia (Spain) in the 1860s

By reconstructing the nutrient balance of a Catalan v illage circa 1861-65 we examine the sustainability of organic agricultural sy stems in the northwest Mediterranean bioregion prior to the green rev olution and the question of whether the nutrients extracted f rom the soil were replenished. With a population density of 59 inhabitants per square km, similar to other northern European rural areas at that time, and a lower liv estock density per cropland unit, this v illage experienced a manure shortage. The gap was f illed by other labour-intensiv e way s of transf erring nutrients f rom uncultiv ated areas into the cropland. Key elements in this agricultural sy stem were v iney ards because they hav e f ew nutrient requirements, and woodland and scrublands as sources of relev ant amounts of nutrients collected in sev eral ways.

Hydrology, light and the use of organic and inorganic materials as structuring factors of biological communities in Mediterranean streams

Hydrological disturbances, light availability and nutrients are the most relevant factors determining the structure of the biological communities in Mediterranean rivers. While some hydrological disturbances are able to induce catastrophic effects, which may cause a complete reset in physical and biological conditions, continued enrichment or changes in light availability are factors leading to the progressive shift in the communities of autotrophs and heterotrophs in the systems. Primary production in Mediterranean streams shows relevant seasonal changes which mainly follows the variations in light availability. In most forested streams, the algal community is shade-adapted. Nutrient enrichment (especially phosphorus) leads to marked increases in primary production, but this increase is not lineal and there is a saturation of algal biomass even in the most enriched systems. The heterotrophs (bacteria, fungi) are related to the pattern of DOC availability (which most depends on the seasonal discharge and leaf fall dynamics) and to the available substrata in the stream. It has been repeatedly observed that shorttime increases of extracellular enzyme activities are related to the accumulation of autochthonous (algal) and/or allochthonous (leaves) organic matter on the streambed during spring and summer, this being more remarkable in dry than in wetter years. Flow reduction favours detritus concentration in pools, and the subsequent increase in the density and biomass of the macroinvertebrate community. In Mediterranean streams collectors are accounting for the highest density and biomass, this being more remarkable in the least permanent systems, in accordance with the effect of floods on the organic matter availability. Nutrients, through the effect on the primary producers, also affect the trophic food web in the streams by favouring the predominance of grazers