Paleomagnetic data and K-Ar ages from Mesozoic units of the Santa Marta massif: A preliminary interpretation for block rotation and translations

We report 6 K-Ar ages and paleomagnetic data from 28 sites collected in Jurassic, Lower Cretaceous and Paleocene rocks of the Santa Marta massif, to test previous hypothesis of rotations and translations of this massif, whose rock assemblage differs from other basement-cored ranges adjacent to the Guyana margin. Three magnetic components were identified in this study. A first component has a direction parallel to the present magnetic field and was uncovered in all units (D 352, I = 25.6, k = 57.35, a95 = 5.3, N = 12). A second component was isolated in Cretaceous limestone and Jurassic volcaniclastic rocks (D = 8.8, I = 8.3, k = 24.71, a95 = 13.7, N = 6), and it was interpreted as of Early Cretaceous age. In Jurassic sites with this component, Early Cretaceous K-Ar ages obtained from this and previous studies are interpreted as reset ages. The third component was uncovered in eight sites of Jurassic volcaniclastic rocks, and its direction indicates negative shallow to moderate inclinations and northeastward declinations. K-Ar ages in these sites are of Early (196.5 +/- 4.9 Ma) to early Late Jurassic age (156.6 +/- 8.9 Ma). Due to local structural complexity and too few Cretaceous outcrops to perform a reliable unconformity test, we only used two sites with (1) K-Ar ages, (2) less structural complexity, and (3) reliable structural data for Jurassic and Cretaceous rocks. The mean direction of the Jurassic component is (D = 20.4, I = -18.2, k = 46.9, a95 = 5.1, n = 18 specimens from two sites). These paleomagnetic data support previous models of northward along-margin translations of Grenvillian-cored massifs. Additionally, clockwise vertical-axis rotation of this massif, with respect to the stable craton, is also documented; the sense of rotation is similar to that proposed for the Perija Range and other ranges of the southern Caribbean margin. More data is needed to confirm the magnitudes of rotations and translations. (C) 2009 Elsevier Ltd. All rights reserved.

Precambrian geotectonic units of the Rio de La Plata craton

The main Precambrian tectonic units of Uruguay include the Piedra Alta tectonostratigraphic terrane (PATT) and Nico Perez tectonostratigraphic terrane (NPTT), separated by the Sarandi del Yi high-strain zone. Both terranes are well exposed in the Rio de La Plata craton (RPC). Although these tectonic units are geographically small, they record a wide span of geologic time. Therefore improved geological knowledge of this area provides a fuller understanding of the evolution of the core of South America. The PATT is constituted by low-to medium-grade metamorphic belts (ca. 2.1 Ga); its petrotectonic associations such as metavolcanic units, conglomerates, banded iron formations, and turbiditic deposits suggest a back-arc or a trench-basin setting. Also in the PATT, a late to post-orogenic, arc-related layered mafic complex (2.3-1.9 Ga), followed by A-type granites (2.08 Ga), and finally a taphrogenic mafic dike swarm (1.78 Ga) occur. The less thoroughly studied NPTT consists of Palaeoproterozoic high-grade metamorphic sequences (ca. 2.2 Ga), mylonites and postorogenic and rapakivi granites (1.75 Ga). The Brasiliano-Pan African orogeny affected this terrane. Neoproterozoic cover occurs in both tectonostratigraphic terranes, but is more developed in the NPTT. Over the past 15 years, new isotopic studies have improved our recognition of different tectonic events and associated processes, such as reactivation of shear zones and fluids circulation. Transamazonian and Statherian tectonic events were recognized in the RPC. Based on magmatism, deformation, basin development and metamorphism, we propose a scheme for the Precambrian tectonic evolution of Uruguay, which is summarized in the first Palaeoproterozoic tectonic map of the Rio de La Plata craton.

ALTERNATING UNITS AS FREE FACTORS IN THE GROUP OF UNITS OF INTEGRAL GROUP RINGS

Let G be a group of odd order that contains a non-central element x whose order is either a prime p >= 5 or 3(l), with l >= 2. Then, in U(ZG), the group of units of ZG, we can find an alternating unit u based on x, and another unit v, which can be either a bicyclic or an alternating unit, such that for all sufficiently large integers m we have that < u(m), v(m)> = < u(m)> * < v(m)> congruent to Z * Z.

Use of Information Visualization Methods Eliminating Cross Talk in Multiple Sensing Units Investigated for a Light-Addressable Potentiometric Sensor

The integration of nanostructured films containing biomolecules and silicon-based technologies is a promising direction for reaching miniaturized biosensors that exhibit high sensitivity and selectivity. A challenge, however, is to avoid cross talk among sensing units in an array with multiple sensors located on a small area. In this letter, we describe an array of 16 sensing units, of a light-addressable potentiometric sensor (LAPS), which was made with layer-by-Layer (LbL) films of a poly(amidomine) dendrimer (PAMAM) and single-walled carbon nanotubes (SWNTs), coated with a layer of the enzyme penicillinase. A visual inspection of the data from constant-current measurements with liquid samples containing distinct concentrations of penicillin, glucose, or a buffer indicated a possible cross talk between units that contained penicillinase and those that did not. With the use of multidimensional data projection techniques, normally employed in information Visualization methods, we managed to distinguish the results from the modified LAPS, even in cases where the units were adjacent to each other. Furthermore, the plots generated with the interactive document map (IDMAP) projection technique enabled the distinction of the different concentrations of penicillin, from 5 mmol L(-1) down to 0.5 mmol L(-1). Data visualization also confirmed the enhanced performance of the sensing units containing carbon nanotubes, consistent with the analysis of results for LAPS sensors. The use of visual analytics, as with projection methods, may be essential to handle a large amount of data generated in multiple sensor arrays to achieve high performance in miniaturized systems.