Evolution of a ~2.7 Ga large igneous province: A volcanological, geochemical and geochronological study of the Agnew Greenstone Belt, and new regional correlations for the Kalgoorlie Terrane (Yilgarn Craton, Western Australia)

The thick package of ~2.7 Ga mafic and ultramafic lavas and intrusions preserved among the Neoarchean of the Kalgoorlie Terrene in Western Australia provides valuable insight into geological processes controlling the most prodigious episode of growth and preservation of juvenile continental crust in Earth’s history. Limited exposure of these rocks results in uncertainty about their age, physical and chemical characteristics, and stratigraphic relationships. This in turn prevents confident correlation of regional occurrences of mafic and ultramafic successions (both intrusive and extrusive) and hinders the interpretation of tectonic setting and magmatic evolution. A recent stratigraphic drilling program of the Neoarchean stratigraphy of the Agnew Greenstone Belt in Western Australia has provided continuous exposures through a c. 7 km thick sequence of mafic and ultramafic units. In this study, we present a volcanological, lithogeochemical and chronological study of the Agnew Greenstone Belt, and provide the first pre-2690 Ma regional correlation across the Kalgoorlie Terrane. The Agnew Greenstone Belt records ~30 m.y. of episodic ultramafic-mafic magmatism that includes two cycles, each defined by a komatiite that is overlain by units that become more evolved and contaminated with time. The sequence is divided into nine conformable packages, each consisting of stacked subaqueous lava flows and comagmatic intrusions, as well as two sills without associated extrusions. Lavas, with the exception of intercalations between two units, form a layer-cake stratigraphy and were likely erupted from a system of fissures tapping the same magma source. The komatiites are not contaminated by continental crust ([La/Sm]PM ~0.7) and are of the Al-undepleted Munro-type. Crustal contamination is evident in many units (Songvang Basalt, Never Can Tell Basalt, Redeemer Basalt, and Turrett Dolerite), as judged by [La/Sm]>1, negative Nb and Ti anomalies, and geochemical mixing trends towards felsic contaminants. Crystal fractionation was also significant, with early olivine and chromite (Mg#>65) followed by plagioclase and clinopyroxene removal (Mg<65), and in the most evolved case, titanomagnetite accumulation. Three new TIMS dates on granophyric zones of mafic sills and one ICP-MS date from an interflow felsic tuff are presented and used for regional stratigraphic correlation. Cycle I magmatism began at ~2720 Ma and ended ~2705 Ma, whereas cycle II began ~2705 Ma and ended at 2690.7±1.2 Ma. Regional correlations indicate the western Kalgoorlie Terrane consists of a remarkably similar stratigraphy that can be recognised at Agnew, Ora Banda and Coolgardie, whereas the eastern part of the terrane (e.g., Kambalda Domain) does not include cycle I, but correlates well with cycle II. This research supports an autochthonous model of greenstone formation, in which one large igneous province, represented by two complete cycles, is constructed on sialic crust. New stratigraphic correlations for the Kalgoorlie Terrane indicate that many units can be traced over distances >100 km, which has implications for exploration targeting for stratigraphically hosted ultramafic Ni and VMS deposits.

The correlation of pore morphology, interconnectivity and physical properties of 3D ceramic scaffolds with bone ingrowth

In the design of tissue engineering scaffolds, design parameters including pore size, shape and interconnectivity, mechanical properties and transport properties should be optimized to maximize successful inducement of bone ingrowth. In this paper we describe a 3D micro-CT and pore partitioning study to derive pore scale parameters including pore radius distribution, accessible radius, throat radius, and connectivity over the pore space of the tissue engineered constructs. These pore scale descriptors are correlated to bone ingrowth into the scaffolds. Quantitative and visual comparisons show a strong correlation between the local accessible pore radius and bone ingrowth; for well connected samples a cutoff accessible pore radius of approximately 100 microM is observed for ingrowth. The elastic properties of different types of scaffolds are simulated and can be described by standard cellular solids theory: (E/E(0))=(rho/rho(s))(n). Hydraulic conductance and diffusive properties are calculated; results are consistent with the concept of a threshold conductance for bone ingrowth. Simple simulations of local flow velocity and local shear stress show no correlation to in vivo bone ingrowth patterns. These results demonstrate a potential for 3D imaging and analysis to define relevant pore scale morphological and physical properties within scaffolds and to provide evidence for correlations between pore scale descriptors, physical properties and bone ingrowth.

Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model

In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Teräsvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. Applying the model to the stock and bond futures data, we discover that the correlation pattern between them has dramatically changed around the turn of the century. The model is also applied to a selection of world stock indices, and we find evidence for an increasing degree of integration in the capital markets.

Improved correlation-based modal strain energy method for global damage detection of truss bridge structures

The previous investigations have shown that the modal strain energy correlation method, MSEC, could successfully identify the damage of truss bridge structures. However, it has to incorporate the sensitivity matrix to estimate damage and is not reliable in certain damage detection cases. This paper presents an improved MSEC method where the prediction of modal strain energy change vector is differently obtained by running the eigensolutions on-line in optimisation iterations. The particular trail damage treatment group maximising the fitness function close to unity is identified as the detected damage location. This improvement is then compared with the original MSEC method along with other typical correlation-based methods on the finite element model of a simple truss bridge. The contributions to damage detection accuracy of each considered mode is also weighed and discussed. The iterative searching process is operated by using genetic algorithm. The results demonstrate that the improved MSEC method suffices the demand in detecting the damage of truss bridge structures, even when noised measurement is considered.

Damage detection for truss bridge structures using correlation-based structural modal strain energy

This paper presents the feasibility of using structural modal strain energy as a parameter employed in correlation- based damage detection method for truss bridge structures. It is an extension of the damage detection method adopting multiple damage location assurance criterion. In this paper, the sensitivity of modal strain energy to damage obtained from the analytical model is incorporated into the correlation objective function. Firstly, the sensitivity matrix of modal strain energy to damage is conducted offline, and for an arbitrary damage case, the correlation coefficient (objective function) is calculated by multiplying the sensitivity matrix and damage vector. Then, a genetic algorithm is used to iteratively search the damage vector maximising the correlation between the corresponding modal strain energy change (hypothesised) and its counterpart in measurement. The proposed method is simulated and compared with the conventional methods, e.g. frequency-error method, coordinate modal assurance criterion and multiple damage location assurance criterion using mode shapes on a numerical truss bridge structure. The result demonstrates the modal strain energy correlation method is able to yield acceptable damage detection outcomes with less computing efforts, even in a noise contaminated condition.