A model to predict land susceptibility to wind erosion in western Queensland,Australia

This paper describes the development and validation of the Australian Land Erodibility Model (AUSLEM), designed to predict land susceptibility to wind erosion in western Queensland, Australia. The model operates at a 5 × 5 km spatial resolution on a daily time-step with inputs of grass and tree cover, soil moisture, soil texture and surficial stone cover. The system was implemented to predict land erodibility, i.e. susceptibility to wind erosion, for the period 1980–1990. Model performance was evaluated using cross-correlation analyses to compare trajectories of mean annual land erodibility at selected locations with trends in wind speed and observational records of dust events and a Dust Storm Index (DSI). The validation was conducted at four spatial length scales from 25 to 150 km using windows to represent potential dust source areas centered on and positioned around eight meteorological stations within the study area. The predicted land erodibility had strong correlations with dust-event frequencies at half of the stations. Poor correlations at the other stations were linked to the inability of the model to account for temporal changes in soil erodibility, and comparing trends in the land erodibility of regions with dust events whose source areas lie outside the regions of interest. The model agreement with dust-event frequency trends was found to vary across spatial scales and was highly dependent on land type characteristics around the stations and on the types of dust events used for validation.     

Electrophysiological assessment of primary cortical neurons genetically engineered using iron oxide nanoparticles

The development of safe technologies to genetically modify neurons is of great interest in regenerative neurology,for both translational and basic science applications.Such approaches have conventionally been heavily reliant on viral transduction methods,which have safety and production limitations.Magnetofection (magnet-assisted gene transfer using iron oxide nanoparticles as vectors) has emerged as a highly promising non-viral alternative for safe and reproducible genetic modification of neurons.Despite the high potential of this technology,there is an important gap in our knowledge of the safety of this approach,namely,whether it alters neuronal function in adverse ways,such as by altering neuronal excitability and signaling.We have investigated the effects of magnetofection in primary cortical neurons by examining neuronal excitability using the whole cell patch clamp technique.We found no evidence that magnetofection alters the voltage-dependent sodium and potassium ionic currents that underpin excitability.Our study provides important new data supporting magnetofection as a safe technology for bioengineering of neuronal cell populations.     

Determinants of voltage attenuation in neocortical pyramidal neuron dendrites

How effectively synaptic and regenerative potentials propagate within neurons depends critically on the membrane properties and intracellular resistivity of the dendritic tree. These properties therefore are important determinants of neuronal function. Here we use simultaneous whole-cell patch-pipette recordings from the soma and apical dendrite of neocortical layer 5 pyramidal neurons to directly measure voltage attenuation in cortical neurons. When combined with morphologically realistic compartmental models of the same cells, the data suggest that the intracellular resistivity of neocortical pyramidal neurons is relatively low ( approximately 70 to 100 Omegacm), but that voltage attenuation is substantial because of nonuniformly distributed resting conductances present at a higher density in the distal apical dendrites. These conductances, which were largely blocked by bath application of CsCl (5 mM), significantly increased steady-state voltage attenuation and decreased EPSP integral and peak in a manner that depended on the location of the synapse. Together these findings suggest that nonuniformly distributed Cs-sensitive and -insensitive resting conductances generate a "leaky" apical dendrite, which differentially influences the integration of spatially segregated synaptic inputs.     

Upper limit ofTc for the copper oxides

The value of the critical temperature of the cuprates correlates with the doping level and is affected by the interplay of two competing factors: (1) the increase in carrier concentration, and (2) the pair-breaking effect of magnetic impurities. An analysis of the temperature dependence of the critical field leads to the conclusion that magnetic impurities are present even in a sample with the maximum observed value ofT _c.A new parameter, intrinsicT _c (T _cintr), which is its value in the absence of magnetic impurities, is introduced. The maximum value ofT _cintr, which corresponds to the maximum doping level, appears to be similar for different cuprates and to be equal to 160–170 K. This is the upper limit ofT _c in the cuprates.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.     

Asymmetric information distances for automated taxonomy construction

A novel method for automatically constructing taxonomies for specific research domains is presented. The proposed methodology uses term co-occurrence frequencies as an indicator of the semantic closeness between terms. To support the automated creation of taxonomies or subject classifications we present a simple modification to the basic distance measure, and describe a set of procedures by which these measures may be converted into estimates of the desired taxonomy. To demonstrate the viability of this approach, a pilot study on renewable energy technologies is conducted, where the proposed method is used to construct a hierarchy of terms related to alternative energy. These techniques have many potential applications, but one activity in which we are particularly interested is the mapping and subsequent prediction of future developments in the technology and research.     

Accelerating geoscience and engineering system simulations on graphics hardware

Many complex natural systems studied in the geosciences are characterized by simple local-scale interactions that result in complex emergent behavior. Simulations of these systems, often implemented in parallel using standard central processing unit (CPU) clusters, may be better suited to parallel processing environments with large numbers of simple processors. Such an environment is found in graphics processing units (GPUs) on graphics cards.This paper discusses GPU implementations of three example applications from computational fluid dynamics, seismic wave propagation, and rock magnetism. These candidate applications involve important numerical modeling techniques, widely employed in physical system simulations, that are themselves examples of distinct computing classes identified as fundamental to scientific and engineering computing. The presented numerical methods (and respective computing classes they belong to) are: (1) a lattice-Boltzmann code for geofluid dynamics (structured grid class); (2) a spectral-finite-element code for seismic wave propagation simulations (sparse linear algebra class); and (3) a least-squares minimization code for interpreting magnetic force microscopy data (dense linear algebra class). Significant performance increases (between 10× and 30× in most cases) are seen in all three applications, demonstrating the power of GPU implementations for these types of simulations and, more generally, their associated computing classes.     

SimpleGrid toolkit: Enabling geosciences gateways to cyberinfrastructure

Cyberinfrastructure science and engineering gateways have become an important modality to connect science and engineering communities and cyberinfrastructure. The use of cyberinfrastructure through gateways is fundamental to the advancement of science and engineering. However, learning science gateway technologies and developing science gateways remain a significant challenge, given that science gateway technologies are still actively evolving and often include a number of sophisticated components. A geosciences gateway must be designed to accommodate legacy methods that geoscientists use in conventional computational tools. The research described in this paper establishes an open-source toolkit—SimpleGrid for learning and developing science gateways based on a service-oriented architecture using a component-based approach that allows flexible separation and integration of the components between geocomputation applications and cyberinfrastructure. The design and implementation of SimpleGrid is based on the National Science Foundation TeraGrid—a key element of the U.S. and world cyberinfrastructure. This paper illustrates our experience of using SimpleGrid and a spatial interpolation method in a tutorial to teach TeraGrid science gateways.     

Assessing tropical cyclone impacts using object-based moderate spatial resolution image analysis: a case study in Bangladesh

The environmental and societal impacts of tropical cyclones could be reduced using a range of management initiatives. Remote sensing can be a cost effective, accurate, and potential tool for mapping the multiple impacts caused by tropical cyclones using high-to-moderate spatial resolution (5–30 m) satellite imagery to provide data on the following essential parameters – evacuation, relief, and management of natural resources. This study developed and evaluated an approach for assessing the impacts of tropical cyclones through object-based image analysis and moderate spatial resolution imagery. Pre- and post-cyclone maps of artificial and natural features are required for assessing the overall impacts in the landscape that could be acquired by mapping specific land cover types. We used the object-based approach to map land-cover types in pre- and post-cyclone Satellite Pour l’Observation de la Terre (SPOT) 5 image data and the post-classification comparison technique to identify changes in the particular features in the landscape. Cyclone Sidr (2007) was used to test the applicability of this approach in Sarankhola Upazila in Bangladesh. The object-based approach provided accurate results for classifying features from pre- and post-cyclone satellite images with an overall accuracy of 95.43% and 93.27%, respectively. Mapped changes identified the extent, type, and form of cyclone induced impacts. Our results indicate that 63.15% of the study area was significantly affected by cyclone Sidr. The majority of mapped damage was found in vegetation, cropped lands, settlements, and infrastructure. The damage results were verified through the high spatial resolution satellite imagery, reports and pictures that were taken after the cyclone. The methods developed may be used in future to assess the multiple impacts caused by tropical cyclones in Bangladesh and other similar environments for the purposes of tropical cyclone disaster management.