Nd-, O-, and H-isotopic evidence for complex, closed-system fluid evolution of the peralkaline Ilimaussaq intrusion, South Greenland

Relatively homogeneous oxygen isotope compositions of amphibole, clinopyroxene, and olivine separates (+5.2 to +5.7parts per thousand relative to VSMOW) and neodymium isotope compositions (epsilon(Nd(T)) = -0.9 to -1.8 for primary magmatic minerals and epsilon(Nd(T)) = -0.1 and -0.5 for mineral separates from late-stage pegmatites and hydrothermal veins) from the alkaline to agpaitic llimaussaq intrusion, South Greenland, indicate a closed system evolution of this igneous complex and support a mantle derivation of the magma. In contrast to the homogeneous oxygen and neodymium isotopic data, deltaD values for hand-picked amphibole separates vary between -92 and -232parts per thousand and are among the most deuterium-depleted values known from igneous amphiboles. The calculated fluid phase coexisting with these amphiboles has a homogeneous oxygen isotopic composition within the normal range of magmatic waters, but extremely heterogeneous and low D/H ratios, implying a decoupling of the oxygen- and hydrogen isotope systems. Of the several possibilities that can account for such unusually low deltaD values in amphiboles (e.g., late-stage hydrothermal exchange with meteoric water, extensive magmatic degassing, contamination with organic matter, and/or effects of Fe-content and pressure on amphibole-water fractionation) the most likely explanation for the range in deltaD values is that the amphiboles have been influenced by secondary interaction and reequilibration with D-depleted fluids obtained through late-magmatic oxidation of internally generated CH(4) and/or H(2). This interpretation is consistent with the known occurrence of abundant magmatic CH(4) in the Ilimaussaq rocks and with previous studies on the isotopic compositions of the rocks and fluids. Copyright (C) 2004 Elsevier Ltd.

Current approaches and challenges for the metabolite profiling of complex natural extracts.

Metabolite profiling is critical in many aspects of the life sciences, particularly natural product research. Obtaining precise information on the chemical composition of complex natural extracts (metabolomes) that are primarily obtained from plants or microorganisms is a challenging task that requires sophisticated, advanced analytical methods. In this respect, significant advances in hyphenated chromatographic techniques (LC-MS, GC-MS and LC-NMR in particular), as well as data mining and processing methods, have occurred over the last decade. Together, these tools, in combination with bioassay profiling methods, serve an important role in metabolomics for the purposes of both peak annotation and dereplication in natural product research. In this review, a survey of the techniques that are used for generic and comprehensive profiling of secondary metabolites in natural extracts is provided. The various approaches (chromatographic methods: LC-MS, GC-MS, and LC-NMR and direct spectroscopic methods: NMR and DIMS) are discussed with respect to their resolution and sensitivity for extract profiling. In addition the structural information that can be generated through these techniques or in combination, is compared in relation to the identification of metabolites in complex mixtures. Analytical strategies with applications to natural extracts and novel methods that have strong potential, regardless of how often they are used, are discussed with respect to their potential applications and future trends.

Management information systems: The balanced scorecard in Spanish public universities

Organisations are becoming increasingly aware of the need for management information systems, due largely to the changing environment and a continuous process of globalisation. All of this means that managers need to adapt the structures of their organisations to the changes and, therefore, to plan, control and manage better. The Spanish public university cannot avoid this changing (demographic, economic and social changes) and globalising (among them the convergence of European qualifications) environment, to which we must add the complex organisation structure, characterised by a high dispersion of authority for decision making in different collegiate and unipersonal organs. It seems obvious that these changes must have repercussions on the direction, organisation and management structures of those public higher education institutions, and it seems natural that, given this environment, the universities must adapt their present management systems to the demand by society for the quality and suitability of the services they provide.

Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex.

Cytotoxic T cell (CTL) activation by antigen requires the specific detection of peptide-major histocompatibility class I (pMHC) molecules on the target-cell surface by the T cell receptor (TCR). We examined the effect of mutations in the antigen-binding site of a Kb-restricted TCR on T cell activation, antigen binding and dissociation from antigen.These parameters were also examined for variants derived from a Kd-restricted peptide that was recognized by a CTL clone. Using these two independent systems, we show that T cell activation can be impaired by mutations that either decrease or increase the binding half-life of the TCR-pMHC interaction. Our data indicate that efficient T cell activation occurs within an optimal dwell-time range of TCR-pMHC interaction. This restricted dwell-time range is consistent with the exclusion of either extremely low or high affinity T cells from the expanded population during immune responses.

A-Kinase Anchoring Protein (AKAP)-Lbc Anchors a PKN-based Signaling Complex Involved in α1-Adrenergic Receptor-induced p38 Activation.

The mitogen-activated protein kinases (MAPKs) pathways are highly organized signaling systems that transduce extracellular signals into a variety of intracellular responses. In this context, it is currently poorly understood how kinases constituting these signaling cascades are assembled and activated in response to receptor stimulation to generate specific cellular responses. Here, we show that AKAP-Lbc, an A-kinase anchoring protein (AKAP) with an intrinsic Rho-specific guanine nucleotide exchange factor activity, is critically involved in the activation of the p38α MAPK downstream of α(1b)-adrenergic receptors (α(1b)-ARs). Our results indicate that AKAP-Lbc can assemble a novel transduction complex containing the RhoA effector PKNα, MLTK, MKK3, and p38α, which integrates signals from α(1b)-ARs to promote RhoA-dependent activation of p38α. In particular, silencing of AKAP-Lbc expression or disrupting the formation of the AKAP-Lbc·p38α signaling complex specifically reduces α(1)-AR-mediated p38α activation without affecting receptor-mediated activation of other MAPK pathways. These findings provide a novel mechanistic hypothesis explaining how assembly of macromolecular complexes can specify MAPK signaling downstream of α(1)-ARs.

Exported oscillator competition: A concept to analyse complex rhytms

We study the interaction between two independent nonlinear oscillators competing through a neutral excitable element. The first oscillator, completely deterministic, acts as a normal pacemaker sending pulses to the neutral element which fires when it is excited by these pulses. The second oscillator, endowed with some randomness, though unable to make the excitable element to beat, leads to the occasional suppression of its firing. The missing beats or errors are registered and their statistics analyzed in terms of the noise intensity and the periods of both oscillators. This study is inspired in some complex rhythms such as a particular class of heart arrhythmia.

Effect of cropping systems in no-till farming on the quality of a Brazilian Oxisol

The no-till system with complex cropping sequences may improve the structural quality and carbon (C) sequestration in soils of the tropics. Thus, the objective of this study was to evaluate the effects of cropping sequences after eight years under the no-till system on the physical properties and C sequestration in an Oxisol in the municipality of Jaboticabal, Sao Paulo, Brazil. A randomized split-block design with three replications was used. The treatments were combinations of three summer cropping sequences - corn/corn (Zea mays L.) (CC), soybean/soybean (Glycine max L. Merryll) (SS), and soybean-corn (SC); and seven winter crops - corn, sunflower (Helianthus annuus L.), oilseed radish (Raphanus sativus L.), pearl millet (Pennisetum americanum (L.) Leeke), pigeon pea (Cajanus cajan (L.) Millsp), grain sorghum (Sorghum bicolor (L.) Moench), and sunn hemp (Crotalaria juncea L.). Soil samples were taken at the 0-10 cm depth after eight years of experimentation. Soil under SC and CC had higher mean weight diameter (3.63 and 3.55 mm, respectively) and geometric mean diameter (3.55 and 2.92 mm) of the aggregates compared to soil under SS (3.18 and 2.46 mm). The CC resulted in the highest soil organic C content (17.07 g kg-1), soil C stock (15.70 Mg ha-1), and rate of C sequestration (0.70 Mg ha-1 yr-1) among the summer crops. Among the winter crops, soil under pigeon pea had the highest total porosity (0.50 m³ m-3), and that under sunn hemp had the highest water stable aggregates (93.74 %). In addition, sunn hemp did not differ from grain sorghum and contained the highest soil organic C content (16.82 g kg-1) and also had the highest rate of C sequestration (0.67 Mg ha-1 yr-1). The soil resistance to penetration was the lower limit of the least limiting water range, while the upper limit was air-filled porosity for soil bulk densities higher than 1.39 kg dm-3 for all cropping sequences. Within the SC sequence, soil under corn and pigeon pea increased least limiting water range by formation of biopores because soil resistance to penetration decreased with the increase in soil bulk density.

Clustering in complex networks. I. General formalism

We develop a full theoretical approach to clustering in complex networks. A key concept is introduced, the edge multiplicity, that measures the number of triangles passing through an edge. This quantity extends the clustering coefficient in that it involves the properties of two¿and not just one¿vertices. The formalism is completed with the definition of a three-vertex correlation function, which is the fundamental quantity describing the properties of clustered networks. The formalism suggests different metrics that are able to thoroughly characterize transitive relations. A rigorous analysis of several real networks, which makes use of this formalism and the metrics, is also provided. It is also found that clustered networks can be classified into two main groups: the weak and the strong transitivity classes. In the first class, edge multiplicity is small, with triangles being disjoint. In the second class, edge multiplicity is high and so triangles share many edges. As we shall see in the following paper, the class a network belongs to has strong implications in its percolation properties.

Simple model for nonexponential relaxation in complex fluids

The nonexponential relaxation occurring in complex dynamics manifested in a wide variety of systems is analyzed through a simple model of diffusion in phase space. It is found that the inability of the system to find its equilibrium state in any time scale becomes apparent in an effective temperature field, which leads to a hierarchy of relaxation times responsible for the slow relaxation phenomena.

Clustering in complex networks. II. Percolation properties

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows us to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the k-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.

Protein-protein interactions between adenovirus DNA polymerase and nuclear factor I mediate formation of the DNA replication preinitiation complex.

The in vitro adenovirus (Ad) DNA replication system provides an assay to study the interaction of viral and host replication proteins with the DNA template in the formation of the preinitiation complex. This initiation system requires in addition to the origin DNA sequences 1) Ad DNA polymerase (Pol), 2) Ad preterminal protein (pTP), the covalent acceptor for protein-primed DNA replication, and 3) nuclear factor I (NFI), a host cell protein identical to the CCAAT box-binding transcription factor. The interactions of these proteins were studied by coimmunoprecipitation and Ad origin DNA binding assays. The Ad Pol can bind to origin sequences only in the presence of another protein which can be either pTP or NFI. While NFI alone can bind to its origin recognition sequence, pTP does not specifically recognize DNA unless Ad Pol is present. Thus, protein-protein interactions are necessary for the targetting of either Ad Pol or pTP to the preinitiation complex. DNA footprinting demonstrated that the Ad DNA site recognized by the pTP.Pol complex was within the first 18 bases at the end of the template which constitutes the minimal origin of replication. Mutagenesis studies have defined the Ad Pol interaction site on NFI between amino acids 68-150, which overlaps the DNA binding and replication activation domain of this factor. A putative zinc finger on the Ad Pol has been mutated to a product that fails to bind the Ad origin sequences but still interacts with pTP. These results indicate that both protein-protein and protein-DNA interactions mediate specific recognition of the replication origin by Ad DNA polymerase.

Time-Temperature Strength-Reaction Product Relationships in Lime-Bentonite-Water Mixtures, HR-111, 1965

The interrelation of curing time, curing temperature, strength, and reactions in lime-bentonite-water mixtures was examined. Samples were molded at constant density and moisture content and then cured for periods of from 1 to 56 days at constant temperatures that ranged from 5C to 60C. After the appropriate curing time the samples were tested for unconfined compressive strength. The broken samples were then analyzed by x-ray diffractometer and spectrophotometer to determine the identity of the reaction products present after each curing period. It was found that the strength gain of lime-clay mixtures cured at different temperatures is due to different phases of the complex reaction, lime & clay to CSH(gel) to CSH(II) to CSH(I) to tobermorite. The farther the reaction proceeds, the higher the strength. There was also evidence of lattice substitutions in the structure of the calcium silicate hydrates at curing temperatures of 50C and higher. No consistent relationship between time, temperature, strength, and the S/A ration of reaction products existed, but in order to achieve high strengths the apparent C/S ration had to be less than two. The curing temperature had an effect on the strength developed by a given amount of reacted silica in the cured lime-clay mixture, but at a given curing temperature the cured sample that had the largest amount of reacted silica gave the highest strength. Evidence was found to indicate that during the clay reaction some calcium is indeed adsorbed onto the clay structure rather than entering into a pozzolanic reaction. Finally, it was determined that it is possible to determine the amount of silica and alumina in lime-clay reaction products by spectrophotometric analysis with sufficient accuracy for comparison purposes. The spectrophotometric analysis techniques used during the investigation were simple and were not time consuming.

Investigation of Field Corrosion Performance and Bond/Development Length of Galvanized Reinforcing Steel, TR-666, 2014

In reinforced concrete systems, ensuring that a good bond between the concrete and the embedded reinforcing steel is critical to long-term structural performance. Without good bond between the two, the system simply cannot behave as intended. The bond strength of reinforcing bars is a complex interaction between localized deformations, chemical adhesion, and other factors. Coating of reinforcing bars, although sometimes debated, has been commonly found to be an effective way to delay the initiation of corrosion in reinforced concrete systems. For many years, the standard practice has been to coat reinforcing steel with an epoxy coating, which provides a barrier between the steel and the corrosive elements of water, air, and chloride ions. Recently, there has been an industry-led effort to use galvanizing to provide the protective barrier commonly provided by traditional epoxy coatings. However, as with any new structural product, questions exist regarding both the structural performance and corrosion resistance of the system. In the fall of 2013, Buchanan County, Iowa constructed a demonstration bridge in which the steel girders and all internal reinforcing steel were galvanized. The work completed in this project sought to understand the structural performance of galvanized reinforcing steel as compared to epoxy-coated steel and to initiate a long-term corrosion monitoring program. This work consisted of a series of controlled laboratory tests and the installation of a corrosion monitoring system that can be observed for years in the future. The results of this work indicate there is no appreciable difference between the bond strength of epoxy-coated reinforcing steel and galvanized reinforcing steel. Although some differences were observed, no notable difference in either peak load, slip, or failure mode could be identified. Additionally, a long-term monitoring system was installed in this Buchanan County bridge and, to date, no corrosion activity has been identified.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.