Showing papers by "University of Adelaide published in 2014"

The global burden of hip and knee osteoarthritis: estimates from the Global Burden of Disease 2010 study

Abstract: Objective To estimate the global burden of hip and knee osteoarthritis (OA) as part of the Global Burden of Disease 2010 study and to explore how the burden of hip and knee OA compares with other conditions. Methods Systematic reviews were conducted to source age-specific and sex-specific epidemiological data for hip and knee OA prevalence, incidence and mortality risk. The prevalence and incidence of symptomatic, radiographic and self-reported hip or knee OA were included. Three levels of severity were defined to derive disability weights (DWs) and severity distribution (proportion with mild, moderate and severe OA). The prevalence by country and region was multiplied by the severity distribution and the appropriate disability weight to calculate years of life lived with disability (YLDs). As there are no deaths directly attributed to OA, YLDs equate disability-adjusted life years (DALYs). Results Globally, of the 291 conditions, hip and knee OA was ranked as the 11th highest contributor to global disability and 38th highest in DALYs. The global age-standardised prevalence of knee OA was 3.8% (95% uncertainty interval (UI) 3.6% to 4.1%) and hip OA was 0.85% (95% UI 0.74% to 1.02%), with no discernible change from 1990 to 2010. Prevalence was higher in females than males. YLDs for hip and knee OA increased from 10.5 million in 1990 (0.42% of total DALYs) to 17.1 million in 2010 (0.69% of total DALYs). Conclusions Hip and knee OA is one of the leading causes of global disability. Methodological issues within this study make it highly likely that the real burden of OA has been underestimated. With the aging and increasing obesity of the world9s population, health professions need to prepare for a large increase in the demand for health services to treat hip and knee OA.

Earth-abundant cocatalysts for semiconductor-based photocatalytic water splitting

Abstract: Photocatalytic water splitting represents a promising strategy for clean, low-cost, and environmental-friendly production of H2 by utilizing solar energy. There are three crucial steps for the photocatalytic water splitting reaction: solar light harvesting, charge separation and transportation, and the catalytic H2 and O2 evolution reactions. While significant achievement has been made in optimizing the first two steps in the photocatalytic process, much less efforts have been put into improving the efficiency of the third step, which demands the utilization of cocatalysts. To date, cocatalysts based on rare and expensive noble metals are still required for achieving reasonable activity in most semiconductor-based photocatalytic systems, which seriously restricts their large-scale application. Therefore, seeking cheap, earth-abundant and high-performance cocatalysts is indispensable to achieve cost-effective and highly efficient photocatalytic water splitting. This review for the first time summarizes all the developed earth-abundant cocatalysts for photocatalytic H2- and O2-production half reactions as well as overall water splitting. The roles and functional mechanism of the cocatalysts are discussed in detail. Finally, this review is concluded with a summary, and remarks on some challenges and perspectives in this emerging area of research.

Hydrogen evolution by a metal-free electrocatalyst

Abstract: Electrocatalytic reduction of water to molecular hydrogen via the hydrogen evolution reaction may provide a sustainable energy supply for the future, but its commercial application is hampered by the use of precious platinum catalysts. All alternatives to platinum thus far are based on nonprecious metals, and, to our knowledge, there is no report about a catalyst for electrocatalytic hydrogen evolution beyond metals. Here we couple graphitic-carbon nitride with nitrogen-doped graphene to produce a metal-free hybrid catalyst, which shows an unexpected hydrogen evolution reaction activity with comparable overpotential and Tafel slope to some of well-developed metallic catalysts. Experimental observations in combination with density functional theory calculations reveal that its unusual electrocatalytic properties originate from an intrinsic chemical and electronic coupling that synergistically promotes the proton adsorption and reduction kinetics.

Metal–Organic Framework Derived Hybrid Co3O4-Carbon Porous Nanowire Arrays as Reversible Oxygen Evolution Electrodes

Abstract: Hybrid porous nanowire arrays composed of strongly interacting Co3O4 and carbon were prepared by a facile carbonization of the metal–organic framework grown on Cu foil. The resulting material, possessing a high surface area of 251 m2 g–1 and a large carbon content of 52.1 wt %, can be directly used as the working electrode for oxygen evolution reaction without employing extra substrates or binders. This novel oxygen evolution electrode can smoothly operate in alkaline solutions (e.g., 0.1 and 1.0 M KOH), affording a low onset potential of 1.47 V (vs reversible hydrogen electrode) and a stable current density of 10.0 mA cm–2 at 1.52 V in 0.1 M KOH solution for at least 30 h, associated with a high Faradaic efficiency of 99.3%. The achieved ultrahigh oxygen evolution activity and strong durability, with superior performance in comparison to the state-of-the-art noble-metal/transition-metal and nonmetal catalysts, originate from the unique nanowire array electrode configuration and in situ carbon incorporati...

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

Abstract: High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

Observation of high-energy astrophysical neutrinos in three years of icecube data

Abstract: A search for high-energy neutrinos interacting within the IceCube detector between 2010 and 2012 provided the first evidence for a high-energy neutrino flux of extraterrestrial origin. Results from an analysis using the same methods with a third year (2012-2013) of data from the complete IceCube detector are consistent with the previously reported astrophysical flux in the 100 TeV-PeV range at the level of 10(-8) GeV cm(-2) s(-1) sr(-1) per flavor and reject a purely atmospheric explanation for the combined three-year data at 5.7 sigma. The data are consistent with expectations for equal fluxes of all three neutrino flavors and with isotropic arrival directions, suggesting either numerous or spatially extended sources. The three-year data set, with a live time of 988 days, contains a total of 37 neutrino candidate events with deposited energies ranging from 30 to 2000 TeV. The 2000-TeV event is the highest-energy neutrino interaction ever observed.

Ancient human genomes suggest three ancestral populations for present-day Europeans

Abstract: We sequenced the genomes of a ∼7,000-year-old farmer from Germany and eight ∼8,000-year-old hunter-gatherers from Luxembourg and Sweden. We analysed these and other ancient genomes with 2,345 contemporary humans to show that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, who contributed ancestry to all Europeans but not to Near Easterners; ancient north Eurasians related to Upper Palaeolithic Siberians, who contributed to both Europeans and Near Easterners; and early European farmers, who were mainly of Near Eastern origin but also harboured west European hunter-gatherer related ancestry. We model these populations' deep relationships and show that early European farmers had ∼44% ancestry from a 'basal Eurasian' population that split before the diversification of other non-African lineages.

FLUSH+RELOAD: a high resolution, low noise, L3 cache side-channel attack

Abstract: Sharing memory pages between non-trusting processes is a common method of reducing the memory footprint of multi-tenanted systems In this paper we demonstrate that, due to a weakness in the Intel X86 processors, page sharing exposes processes to information leaks We present FLUSH+RELOAD, a cache side-channel attack technique that exploits this weakness to monitor access to memory lines in shared pages Unlike previous cache side-channel attacks, FLUSH+RELOAD targets the Last-Level Cache (ie L3 on processors with three cache levels) Consequently, the attack program and the victim do not need to share the execution core We demonstrate the efficacy of the FLUSH+RELOAD attack by using it to extract the private encryption keys from a victim program running GnuPG 1413 We tested the attack both between two unrelated processes in a single operating system and between processes running in separate virtual machines On average, the attack is able to recover 967% of the bits of the secret key by observing a single signature or decryption round

Toward Design of Synergistically Active Carbon-Based Catalysts for Electrocatalytic Hydrogen Evolution

Abstract: Replacement of precious Pt catalyst with cost-effective alternatives would be significantly beneficial for hydrogen production via electrocatalytic hydrogen evolution reaction (HER). All candidates thus far are exclusively metallic catalysts, which suffer inherent corrosion and oxidation susceptibility during acidic proton-exchange membrane electrolysis. Herein, based on theoretical predictions, we designed and synthesized nitrogen (N) and phosphorus (P) dual-doped graphene as a nonmetallic electrocatalyst for sustainable and efficient hydrogen production. The N and P heteroatoms could coactivate the adjacent C atom in the graphene matrix by affecting its valence orbital energy levels to induce a synergistically enhanced reactivity toward HER. As a result, the dual-doped graphene showed higher electrocatalytic HER activity than single-doped ones and comparable performance to some of the traditional metallic catalysts.

Origin of the electrocatalytic oxygen reduction activity of graphene-based catalysts: a roadmap to achieve the best performance.

Abstract: The mutually corroborated electrochemical measurements and density functional theory (DFT) calculations were used to uncover the origin of electrocatalytic activity of graphene-based electrocatalysts for oxygen reduction reaction (ORR). A series of graphenes doped with nonmetal elements was designed and synthesized, and their ORR performance was evaluated in terms of four electrochemical descriptors: exchange current density, on-set potential, reaction pathway selectivity and kinetic current density. It is shown that these descriptors are in good agreement with DFT calculations, allowing derivation of a volcano plot between the ORR activity and the adsorption free energy of intermediates on metal-free materials, similarly as in the case of metallic catalysts. The molecular orbital concept was used to justify this volcano plot, and to theoretically predict the ORR performance of an ideal graphene-based catalyst, the ORR activity of which is comparable to the state-of-the-art Pt catalyst. Moreover, this study may stimulate the development of metal-free electrocatalysts for other key energy conversion processes including hydrogen evolution and oxygen evolution reactions and largely expand the spectrum of catalysts for energy-related electrocatalysis reactions.

Future changes to the intensity and frequency of short‐duration extreme rainfall

Abstract: Evidence that extreme rainfall intensity is increasing at the global scale has strengthened considerably in recent years Research now indicates that the greatest increases are likely to occur in short-duration storms lasting less than a day, potentially leading to an increase in the magnitude and frequency of flash floods This review examines the evidence for subdaily extreme rainfall intensification due to anthropogenic climate change and describes our current physical understanding of the association between subdaily extreme rainfall intensity and atmospheric temperature We also examine the nature, quality, and quantity of information needed to allow society to adapt successfully to predicted future changes, and discuss the roles of observational and modeling studies in helping us to better understand the physical processes that can influence subdaily extreme rainfall characteristics We conclude by describing the types of research required to produce a more thorough understanding of the relationships between local-scale thermodynamic effects, large-scale atmospheric circulation, and subdaily extreme rainfall intensity

The evolution of lncRNA repertoires and expression patterns in tetrapods

Abstract: Only a very small fraction of long noncoding RNAs (lncRNAs) are well characterized. The evolutionary history of lncRNAs can provide insights into their functionality, but the absence of lncRNA annotations in non-model organisms has precluded comparative analyses. Here we present a large-scale evolutionary study of lncRNA repertoires and expression patterns, in 11 tetrapod species. We identify approximately 11,000 primate-specific lncRNAs and 2,500 highly conserved lncRNAs, including approximately 400 genes that are likely to have originated more than 300 million years ago. We find that lncRNAs, in particular ancient ones, are in general actively regulated and may function predominantly in embryonic development. Most lncRNAs evolve rapidly in terms of sequence and expression levels, but tissue specificities are often conserved. We compared expression patterns of homologous lncRNA and protein-coding families across tetrapods to reconstruct an evolutionarily conserved co-expression network. This network suggests potential functions for lncRNAs in fundamental processes such as spermatogenesis and synaptic transmission, but also in more specific mechanisms such as placenta development through microRNA production.

Graphitic carbon nitride nanosheet-carbon nanotube three-dimensional porous composites as high-performance oxygen evolution electrocatalysts.

Abstract: A new class of highly efficient oxygen evolution catalysts has been synthesized through the self-assembly of graphitic carbon nitride nanosheets and carbon nanotubes, driven by π-π stacking and electrostatic interactions. Remarkably, the catalysts exhibit higher catalytic oxygen evolution activity and stronger durability than Ir-based noble-metal catalysts and display the best performance among the reported nonmetal catalysts. This good result is attributed to the high nitrogen content and the efficient mass and charge transfer in the porous three-dimensional nanostructure.

Deep Convolutional Neural Fields for Depth Estimation from a Single Image

Abstract: We consider the problem of depth estimation from a single monocular image in this work. It is a challenging task as no reliable depth cues are available, e.g., stereo correspondences, motions, etc. Previous efforts have been focusing on exploiting geometric priors or additional sources of information, with all using hand-crafted features. Recently, there is mounting evidence that features from deep convolutional neural networks (CNN) are setting new records for various vision applications. On the other hand, considering the continuous characteristic of the depth values, depth estimations can be naturally formulated into a continuous conditional random field (CRF) learning problem. Therefore, we in this paper present a deep convolutional neural field model for estimating depths from a single image, aiming to jointly explore the capacity of deep CNN and continuous CRF. Specifically, we propose a deep structured learning scheme which learns the unary and pairwise potentials of continuous CRF in a unified deep CNN framework. The proposed method can be used for depth estimations of general scenes with no geometric priors nor any extra information injected. In our case, the integral of the partition function can be analytically calculated, thus we can exactly solve the log-likelihood optimization. Moreover, solving the MAP problem for predicting depths of a new image is highly efficient as closed-form solutions exist. We experimentally demonstrate that the proposed method outperforms state-of-the-art depth estimation methods on both indoor and outdoor scene datasets.

Nitrogen and Oxygen Dual‐Doped Carbon Hydrogel Film as a Substrate‐Free Electrode for Highly Efficient Oxygen Evolution Reaction

Abstract: A three-dimensional (3D) electrode composed of nitrogen, oxygen dualdoped graphene-carbon nanotube hydrogel film is fabricated, which greatly favors the transport and access of gas and reaction intermediates, and shows a remarkable oxygen-evolution catalytic performance in both alkaline and acidic solutions.

Ultrasensitive terahertz sensing with high-Q Fano resonances in metasurfaces

Abstract: High quality factor resonances are extremely promising for designing ultra-sensitive refractive index label-free sensors, since it allows intense interaction between electromagnetic waves and the analyte material. Metamaterial and plasmonic sensing have recently attracted a lot of attention due to subwavelength confinement of electromagnetic fields in the resonant structures. However, the excitation of high quality factor resonances in these systems has been a challenge. We excite an order of magnitude higher quality factor resonances in planar terahertz metamaterials that we exploit for ultrasensitive sensing. The low-loss quadrupole and Fano resonances with extremely narrow linewidths enable us to measure the minute spectral shift caused due to the smallest change in the refractive index of the surrounding media. We achieve sensitivity levels of 7.75 × 103 nm/refractive index unit (RIU) with quadrupole and 5.7 × 104 nm/RIU with the Fano resonances which could be further enhanced by using thinner substrates. These findings would facilitate the design of ultrasensitive real time chemical and biomolecular sensors in the fingerprint region of the terahertz regime.

Refining analyses of copy number variation identifies specific genes associated with developmental delay

Abstract: Copy number variants (CNVs) are associated with many neurocognitive disorders; however, these events are typically large, and the underlying causative genes are unclear. We created an expanded CNV morbidity map from 29,085 children with developmental delay in comparison to 19,584 healthy controls, identifying 70 significant CNVs. We resequenced 26 candidate genes in 4,716 additional cases with developmental delay or autism and 2,193 controls. An integrated analysis of CNV and single-nucleotide variant (SNV) data pinpointed 10 genes enriched for putative loss of function. Follow-up of a subset of affected individuals identified new clinical subtypes of pediatric disease and the genes responsible for disease-associated CNVs. These genetic changes include haploinsufficiency of SETBP1 associated with intellectual disability and loss of expressive language and truncations of ZMYND11 in individuals with autism, aggression and complex neuropsychiatric features. This combined CNV and SNV approach facilitates the rapid discovery of new syndromes and genes involved in neuropsychiatric disease despite extensive genetic heterogeneity.

The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties

Abstract: This review addresses the applicability of visible (Vis), near-infrared (NIR), and mid-infrared (MIR) reflectance spectroscopy for the prediction of soil properties. We address (1) the properties that can be predicted and the accuracy of the predictions, (2) the most suitable spectral regions for specific soil properties, (3) the number of predictions reported for each property, and (4) in-field versus laboratory spectral techniques.We found the following properties to be successfully predicted: soil water content, texture, soil carbon (C), cation exchange capacity, calcium and magnesium (exchangeable), total nitrogen (N), pH, concentration of metals/metalloids, microbial size, and activity. Generally, MIR produced better predictions than Vis-NIR, but Vis-NIR outperformed MIR for a number of properties (e.g., biological). An advantage of Vis-NIR is instrument portability although a new range of MIR portable devices is becoming available. In-field predictions for clay, water, total organic C, extra...

High-Sensitivity Metamaterial-Inspired Sensor for Microfluidic Dielectric Characterization

Abstract: A new metamaterial-inspired microwave microfluidic sensor is proposed in this paper. The main part of the device is a microstrip coupled complementary split-ring resonator (CSRR). At resonance, a strong electric field will be established along the sides of CSRR producing a very sensitive area to a change in the nearby dielectric material. A micro-channel is positioned over this area for microfluidic sensing. The liquid sample flowing inside the channel modifies the resonance frequency and peak attenuation of the CSRR resonance. The dielectric properties of the liquid sample can be estimated by establishing an empirical relation between the resonance characteristics and the sample complex permittivity. The designed microfluidic sensor requires a very small amount of sample for testing since the cross-sectional area of the sensing channel is over five orders of magnitude smaller than the square of the wavelength. The proposed microfluidic sensing concept is compatible with lab-on-a-chip platforms owing to its compactness.

Evolutionary algorithms and other metaheuristics in water resources

Abstract: The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

Post-synthetic metalation of metal–organic frameworks

Abstract: Post-synthetic metalation (PSMet) offers expansive scope for a targeted approach to tailoring the properties of MOFs. Numerous methods for carrying-out PSMet chemistry have been reported, however, these can be categorized into three general strategies: (a) addition to coordinating groups; (b) counter-ion exchange in charged frameworks; or, (c) host–guest encapsulation of metal-containing entities within the pores of the framework. PSMet has been applied to enhance the performance characteristics of parent MOFs for gas storage and separation, and catalysis. Notably, PSMet is a prominent strategy in the field of MOF catalysis as it offers a route to design size-selective catalysts, based on the premise of reticular chemistry in MOFs and the ability to incorporate a range of catalytically-active metal centres. Other applications for materials produced via or utilising PSMet strategies include enhancing gas storage or molecular separations, the triggered release of drugs, sensing and tunable light emission for luminescent materials. This review surveys seminal examples of PSMet to highlight the broad scope of this technique for enhancing the performance characteristics of MOFs and to demonstrate how the PSMet concept can be developed for future applications.

Aquaporins: Highly Regulated Channels Controlling Plant Water Relations

Abstract: Plant growth and development are dependent on tight regulation of water movement. Water diffusion across cell membranes is facilitated by aquaporins that provide plants with the means to rapidly and reversibly modify water permeability. This is done by changing aquaporin density and activity in the membrane, including posttranslational modifications and protein interaction that act on their trafficking and gating. At the whole organ level aquaporins modify water conductance and gradients at key “gatekeeper” cell layers that impact on whole plant water flow and plant water potential. In this way they may act in concert with stomatal regulation to determine the degree of isohydry/anisohydry. Molecular, physiological, and biophysical approaches have demonstrated that variations in root and leaf hydraulic conductivity can be accounted for by aquaporins but this must be integrated with anatomical considerations. This Update integrates these data and emphasizes the central role played by aquaporins in regulating plant water relations.

Anaerobic digestion of algae biomass: A review

Abstract: The anaerobic digestion of microalgae is a prospective environmentally feasible option for creating a renewable source of energy for industrial and domestic needs. Microalgae anaerobic digestion is a key unit process that integrates efficiency and beneficially into the production of microalgae derived biofuels. Anaerobic digestion culminating in methane fermentation improves the economic viability of microalgae liquid biofuel production and presents an opportunity for power generation from wastewater derived microalgae. However the anaerobic digestion of microalgae biomass is not straight forward due to several technical restraints including low concentration of digestible biodegradable substrate, recalcitrant substrate constituents, cell wall degradability, low carbon to nitrogen ratio, ammonia toxicity and effects from salinity and associated metal ions. Current production methods for liquid biofuel production from microalgae produce approximately 60–70% residual biomass that is currently a byproduct. Anaerobic digestion provides biogas, but it can also provide essential nutrient recovery from lipid extracted microalgae biomass. The biogas produced from the anaerobic digestion process can be used to generate onsite electrical power or thermal heat to offset biomass processing and extraction processes. When both of these processes are integrated and operated simultaneously, the benefits to microalgae biofuel production and wastewater treatment derived energy production are increased significantly. To consider the integration of anaerobic digestion into a commercial-scale integrated microalgae production and biofuel refinery facility or wastewater treatment plant we present a review of the literature, the current state of the art and future directions for research.

Fe-N decorated hybrids of CNTs grown on hierarchically porous carbon for high-performance oxygen reduction.

Abstract: An Fe-N-decorated hybrid material of carbon nanotubes (CNTs) grown in situ from porous carbon microblocks is designed and constructed. This material successfully combines the desirable merits for oxygen reduction reaction (ORR), such as highly active Fe-N species, good conductivity, large pore size, and sufficient surface area. These structural advantages give this low-priced material an outstanding catalytic performance for ORR closely comparable with Pt/C of the same quantity.

Observation of active sites for oxygen reduction reaction on nitrogen-doped multilayer graphene

Abstract: Active sites and the catalytic mechanism of nitrogen-doped graphene in an oxygen reduction reaction (ORR) have been extensively studied but are still inconclusive, partly due to the lack of an experimental method that can detect the active sites. It is proposed in this report that the active sites on nitrogen-doped graphene can be determined via the examination of its chemical composition change before and after ORR. Synchrotron-based X-ray photoelectron spectroscopy analyses of three nitrogen-doped multilayer graphene samples reveal that oxygen reduction intermediate OH(ads), which should chemically attach to the active sites, remains on the carbon atoms neighboring pyridinic nitrogen after ORR. In addition, a high amount of the OH(ads) attachment after ORR corresponds to a high catalytic efficiency and vice versa. These pinpoint that the carbon atoms close to pyridinic nitrogen are the main active sites among the different nitrogen doping configurations.