Dynamic subsidence of Eastern Australia during the Cretaceous

During the Early Cretaceous Australia's eastward passage over sinking subducted slabs induced widespread dynamic subsidence and formation of a large epeiric sea in the eastern interior. Despite evidence for convergence between Australia and the paleo-Pacific, the subduction zone location has been poorly constrained. Using coupled plate tectonic–mantle convection models, we test two end-member scenarios, one with subduction directly east of Australia's reconstructed continental margin, and a second with subduction translated ~ 1000 km east, implying the existence of a back-arc basin. Our models incorporate a rheological model for the mantle and lithosphere, plate motions since 140 Ma and evolving plate boundaries. While mantle rheology affects the magnitude of surface vertical motions, timing of uplift and subsidence depends on plate boundary geometries and kinematics. Computations with a proximal subduction zone result in accelerated basin subsidence occurring 20 Myr too early compared with tectonic subsidence calculated from well data. This timing offset is reconciled when subduction is shifted eastward. Comparisons between seismic tomography and model temperature cross-sections, and an absence of subduction zone volcanism in eastern Australia in the Early Cretaceous provide support for the back-arc basin scenario.     

Biogeographical Patterns of Marine Benthic Macroinvertebrates Along the Atlantic Coast of the Northeastern USA

The biogeography of marine benthic macroinvertebrates of US Atlantic estuaries and inshore coastal areas from Delaware Bay north to Passamaquoddy Bay was studied to compare recent data with historical biogeographic studies, define physical–chemical factors affecting species’ distributions, and provide information for calibrating benthic indices of environmental condition. Five years (2000–2004) of data from 614 non-polluted, soft-bottom stations from the National Coastal Assessment were analyzed. Multi-dimensional scaling done on Bray-Curtis similarity matrices of species’ relative abundance (547 species) suggested seven subregions: two based on salinity (oligohaline, mesohaline) and five based on latitude. Species’ distribution patterns for stations with salinities ≥18 (n = 558) were strongly influenced by latitude; Cape Cod was a clear faunal transition zone (R = 0.92, p < 0.001). Conversely, for stations with salinities <18 (n = 56), salinity was the more important factor. An ordination of abiotic variables (temperature, salinity, sediment percent silt-clay, depth) correlated well with the ordination of species’ relative abundance data (R = 0.77, p < 0.001). The first split of a multivariate regression tree was by a summer bottom temperature of 20°C at Cape Cod. Salinity and percent silt-clay led to further splits. These results support the existence of Virginian and Transhatteran biogeographic provinces. They constitute a baseline for addressing broad-scale and long-term issues such as global climate change, species invasions, and conservation planning.     

Fading Hawking radiation

In this study, we explore a particular type Hawking radiation which ends with zero temperature and entropy. The appropriate black holes for this purpose are the linear dilaton black holes. In addition to the black hole choice, a recent formalism in which the Parikh-Wilczek’s tunneling formalism amalgamated with quantum corrections to all orders in ? is considered. The adjustment of the coefficients of the quantum corrections plays a crucial role on this particular Hawking radiation. The obtained tunneling rate indicates that the radiation is not pure thermal anymore, and hence correlations of outgoing quanta are capable of carrying away information encoded within them. Finally, we show in detail that when the linear dilaton black hole completely evaporates through such a particular radiation, entropy of the radiation becomes identical with the entropy of the black hole, which corresponds to “no information loss”.     

The photometric method of extrasolar planet detection revisited

We investigate the geometry concerning the photometric method of extrasolar planet detection, i.e., the detection of dimunition of a parent star's brightness during a planetary transit. Under the assumption that planetary orbital inclinations can be defined by a Gaussian with a of 10° centered on the parent star's equatorial plane, Monte Carlo simulations suggest that for a given star observed at an inclination of exactly 90°, the probability of at least one Earth-sized or larger planet being suitably placed for transits is approximately 4%. This probability drops to 3% for a star observed at an inclination of 80°, and is still 0.5% for a star observed at an inclination of 60°. If one can select 100 stars with a pre-determined inclination 80°, the probability of at least one planet being suitably configured for transits is 95%. The majority of transit events are due to planets in small-a orbits similar to the Earth and Venus; thus, the photometric method in principle is the method best suited for the detection of Earthlike planets.The photometric method also allows for testing whether or not planets can exist within binary systems. This can be done by selecting binary systems observed at high orbital inclinations, both eclipsing binaries and wider visual binaries. For a real-world example, we look at the Centauri system (i = 79°.2). If we assume that the equatorial planes of both components coincide with the system's orbital plane, Monte Carlo simulations suggest that the probability of at least one planet (of either component) being suitably configured for transits is approximately 8%.In conclusion, we present a non-exhaustive list of solar-type stars, both single and within binary systems, which exhibit a high equatorial inclination. These objects may be considered as preliminary candidates for planetary searches via the photometric method.Paper presented at the Conference onPlanetary Systems: Formation, Evolution, and Detection held 7–10 December, 1992 at CalTech, Pasadena, California, U.S.A.     

A statistical model for spatial patterns of Buruli ulcer in the Amansie West district,Ghana

Buruli ulcer (BU), a skin ulceration caused by Mycobacterium ulcerans (MU), is the second most widespread mycobacterium infection in Ghana. Its infection pathway is possibly related to the potable and agricultural water supply. This study aims to identify environmental factors that influence infection in a part of Ghana. It examines the significance of contaminated surface drainage channels and groundwater using conditional autoregressive (CAR) statistical modelling. This type of modelling implies that the spatial pattern of BU incidence in one community depends on the influence of the environment in neighbouring communities. Covariates were included to assess the spatial relationship between environmental risk factors and BU incidence in the study area. The study reveals an association between (a) the mean As content of soil and spatial distribution of BU and (b) the distance to sites of gold mining and spatial distribution of BU. We conclude that both arsenic in the natural environment and gold mining influence BU infection.     

Artificial Neural Networks for Mineral-Potential Mapping: A Case Study from Aravalli Province,Western India

This paper describes a GIS-based application of a radial basis functional link net (RBFLN) to map the potential of SEDEX-type base metal deposits in a study area in the Aravalli metallogenic province (western India). Available public domain geodata of the study area were processed to generate evidential maps, which subsequently were encoded and combined to derive a set of input feature vectors. A subset of feature vectors with known targets (i.e., either known mineralized or known barren locations) was extracted and divided into (a) a training data set and (b) a validation data set. A series of RBFLNs were trained to determine the network architecture and estimate parameters that mapped the maximum number of validation vectors correctly to their respective targets. The trained RBFLN that gave the best performance for the validation data set was used for processing all feature vectors. The output for each feature vector is a predictive value between 1 and 0, indicating the extent to which a feature vector belongs to either the mineralized or the barren class. These values were mapped to generate a predictive classification map, which was reclassified into a favorability map showing zones with high, moderate and low favorability for SEDEX-type base metal deposits in the study area. The method demarcates successfully high favorability zones, which occupy 6% of the study area and contain 94% of the known base metal deposits.     

A Hybrid Neuro-Fuzzy Model for Mineral Potential Mapping

A GIS-based hybrid neuro-fuzzy approach to mineral potential mapping implements a Takagi–Sugeno type fuzzy inference system in a four-layered feed-forward adaptive neural network. In this approach, each unique combination of predictor patterns is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent predictor patterns. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location), extracted from a set of all feature vectors, is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a favorability map. The procedure is applied to regional-scale base metal potential mapping in a study area located in the Aravalli metallogenic province (western India). The adaptive neuro-fuzzy inference system demarcates high favorability zones occupying 9.75% of the study area and identifies 96% of the known base metal deposits. This result is significant both in terms of reduction in search area and the percentage of deposits identified.     

Numerical modelling experiments in vapour geochemistry. II: Vapour dispersion patterns and exploration implications

This study examines the development of vapour anomalies in one-layer and two-layer media overlying vapour sources having different shapes and different time-dependent stabilities. Theoretical concentration patterns are computed using two-dimensional finite-difference numerical solutions of the diffusion equation. Calculated diffusion patterns are compared with in vitro experimental data, and their general features are shown to be comparable. Results are discussed in terms of possible applications to vapour geochemistry in mineral exploration, with particular reference to the detection at the surface of buried mineral deposits.     

Where Are Porphyry Copper Deposits Spatially Localized? A Case Study in Benguet Province,Philippines

To provide guides for exploration of porphyry copper mineralization at a district scale, we examine the spatial association between known porphyry copper deposits and geologic features in Benguet, Philippines. The spatial associations between the porphyry copper deposits and strike-slip fault discontinuities, batholithic pluton margins and porphyry plutons are quantified using weights of evidence modeling. In the training and testing district, the porphyry copper occurrences are associated spatially with strike-slip fault discontinuities, batholithic pluton margins and contacts of porphyry plutons within distances of 3 km, 2.25 km, and 1 km, respectively. In addition, the porphyry plutons are associated spatially with strike-slip fault discontinuities and contacts of batholithic plutons within a distance of 2.25 km and 3 km, respectively. Based on these significant spatial associations, predictive maps are generated to delineate zones favorable for porphyry copper mineralization and zones favorable for emplacement of porphyry plutons in Benguet province, Philippines. Validations of the predictive models demonstrate their efficacy in pointing to zones for subsequent follow-up exploration work.