Rainfall variability drives interannual variation in N2O emissions from a humid, subtropical pasture

Variations in interannual rainfall totals can lead to large uncertainties in annual N2O emission budget estimates from short term field studies. The interannual variation in nitrous oxide (N2O) emissions from a subtropical pasture in Queensland, Australia, was examined using continuous measurements of automated chambers over 2 consecutive years. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than soil water content. Over 48% of the total N2O emitted was lost in just 16% of measurement days. Interannual variation in annual N2O estimates was high, with cumulative emissions increasing with decreasing rainfall. Cumulative emissions averaged 1826.7 ± 199.9 g N2O-N ha−1 yr−1 over the two year period, though emissions from 2008 (2148 ± 273 g N2O-N ha−1 yr−1) were 42% higher than 2007 (1504 ± 126 g N2O-N ha−1 yr−1). This increase in annual emissions coincided with almost half of the summer precipitation from 2007 to 2008. Emissions dynamics were chiefly driven by the distribution and size of rain events which varied on a seasonal and annual basis. Sampling frequency effects on cumulative N2O flux estimation were assessed using a jackknife technique to inform future manual sampling campaigns. Test subsets of the daily measured data were generated for the pasture and two adjacent land-uses (rainforest and lychee orchard) by selecting measured flux values at regular time intervals ranging from 1 to 30 days. Errors associated with weekly sampling were up to 34% of the sub-daily mean and were highly biased towards overestimation if strategically sampled following rain events. Sampling time of day also played a critical role. Morning sampling best represented the 24 hour mean in the pasture, whereas sampling at noon proved the most accurate in the shaded rainforest and lychee orchard.

Large variations in the Holocene marine radiocarbon reservoir effect reflect ocean circulation and climatic changes

Accurate radiocarbon dating of marine samples requires knowledge of the marine radiocarbon reservoir effect. This effect for a particular site/region is generally assumed constant through time when calibrating marine 14C ages. However, recent studies have shown large temporal variations of several hundred to a couple of thousand years in this effect for a number of regions during the late Quaternary and Holocene. Here we report marine radiocarbon reservoir correction (ΔRΔR) for Heron Reef and Moreton Bay in southwestern (SW) Pacific for the last 8 ka derived from 14C analysis of 230Th-dated corals. Most of our ΔRΔR for the last ∼5.4 ka agree well with their modern value, but large ΔRΔR variability of ∼410 yr (from trough to peak) with possible decadal/centennial fluctuations is evident for the period ∼5.4–8 ka. The latter time interval also has significant variations with similar features in previously published ΔRΔR values for other sites in the Pacific, including southern Peru–northern Chile in southeastern (SE) Pacific, the South China Sea, Vanuatu and Papua New Guinea, with the largest magnitude of ∼920 yr from SE Pacific. The mechanisms for these large ΔRΔR variations across the Pacific during the mid-Holocene are complex processes involving (1) changes in the quantity and 14C content of upwelled waters in tropical east Pacific (TEP) (frequency and intensity of ocean upwelling in the TEP, and contribution of Subantarctic Mode Water to the upwelled waters, which is influenced by the intensity and position of southern westerly winds), and (2) variations in ocean circulation associated with climate change (La Niña/El Niño conditions, intensity of easterly trade winds, positions of the Intertropical Convergence Zone and the South Pacific Convergence Zone), which control the spreading of the older upwelled surface waters in the TEP to the western sites. Our results imply the need for employing temporal changes in ΔRΔR values, instead of constant (modern) values, for age calibration of Holocene marine samples not only for the SW Pacific sites but also for other tropical and subtropical sites in the Pacific.

Lateralization of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging and machine learning

Lateralization of temporal lobe epilepsy (TLE) is critical for successful outcome of surgery to relieve seizures. TLE affects brain regions beyond the temporal lobes and has been associated with aberrant brain networks, based on evidence from functional magnetic resonance imaging. We present here a machine learning-based method for determining the laterality of TLE, using features extracted from resting-state functional connectivity of the brain. A comprehensive feature space was constructed to include network properties within local brain regions, between brain regions, and across the whole network. Feature selection was performed based on random forest and a support vector machine was employed to train a linear model to predict the laterality of TLE on unseen patients. A leave-one-patient-out cross validation was carried out on 12 patients and a prediction accuracy of 83% was achieved. The importance of selected features was analyzed to demonstrate the contribution of resting-state connectivity attributes at voxel, region, and network levels to TLE lateralization.

Quantifying the state of populations and effects of disturbances at large spatio-temporal scales: The case of coral populations in the great barrier reef

This project was a step forward in applying statistical methods and models to provide new insights for more informed decision-making at large spatial scales. The model has been designed to address complicated effects of ecological processes that govern the state of populations and uncertainties inherent in large spatio-temporal datasets. Specifically, the thesis contributes to better understanding and management of the Great Barrier Reef.

Quantification of stability in an agility drill using linear and nonlinear measures of variability

This study implemented linear and nonlinear methods of measuring variability to determine differences in stability of two groups of skilled (n = 10) and unskilled (n = 10) participants performing 3m forward/backward shuttle agility drill. We also determined whether stability measures differed between the forward and backward segments of the drill. Finally, we sought to investigate whether local dynamic stability, measured using largest finite-time Lyapunov exponents, changed from distal to proximal lower extremity segments. Three-dimensional coordinates of five lower extremity markers data were recorded. Results revealed that the Lyapunov exponents were lower (P < 0.05) for skilled participants at all joint markers indicative of higher levels of local dynamic stability. Additionally, stability of motion did not differ between forward and backward segments of the drill (P > 0.05), signifying that almost the same control strategy was used in forward and backward directions by all participants, regardless of skill level. Furthermore, local dynamic stability increased from distal to proximal joints (P < 0.05) indicating that stability of proximal segments are prioritized by the neuromuscular control system. Finally, skilled participants displayed greater foot placement standard deviation values (P < 0.05), indicative of adaptation to task constraints. The results of this study provide new methods for sport scientists, coaches to characterize stability in agility drill performance.

Increasing functional variability in the preparatory phase of the takeoff improves elite springboard diving performance

PURPOSE: Previous research demonstrating that specific performance outcome goals can be achieved in different ways is functionally significant for springboard divers whose performance environment can vary extensively. This body of work raises questions about the traditional approach of balking (terminating the takeoff) by elite divers aiming to perform only identical, invariant movement patterns during practice. METHOD: A 12-week training program (2 times per day; 6.5 hr per day) was implemented with 4 elite female springboard divers to encourage them to adapt movement patterns under variable takeoff conditions and complete intended dives, rather than balk. RESULTS: Intraindividual analyses revealed small increases in variability in the board-work component of each diver's pretraining and posttraining program reverse-dive takeoffs. No topological differences were observed between movement patterns of dives completed pretraining and posttraining. Differences were noted in the amount of movement variability under different training conditions (evidenced by higher normalized root mean square error indexes posttraining). An increase in the number of completed dives (from 78.91%-86.84% to 95.59%-99.29%) and a decrease in the frequency of balked takeoffs (from 13.16%-19.41% to 0.63%-4.41%) showed that the elite athletes were able to adapt their behaviors during the training program. These findings coincided with greater consistency in the divers' performance during practice as scored by qualified judges. CONCLUSION: Results suggested that on completion of training, athletes were capable of successfully adapting their movement patterns under more varied takeoff conditions to achieve greater consistency and stability of performance outcomes.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

Temporal trend of pesticide concentrations in the Chikugo River (Japan) with changes in environmental regulation and field infrastructure

Contamination of pesticides, which are applied to rice paddy fields, in river water has been a major problem in Japan for decades. A prolonged water holding period after pesticide application in paddy fields is expected to reduce the concentration of rice pesticides in river water. Therefore, a long monitoring campaign was conducted from 2004 to 2010 to measure the concentrations of pesticides in water samples collected from several points along the Chikugo River (Japan) including tributaries and the main stream to see if there was any reduction in the level of pesticide contamination after the extension of the water holding period (from 3–4 days to 7 days) was introduced in 2007 by the new water management regulation. No significant difference (p > 0.05) was found in pesticide concentrations between the periods before and after 2007 in all monitoring points, except in one tributary where the pesticide concentrations after 2007 were even higher than that of the previous period. A detailed study in one of the tributaries also revealed that the renovated infrastructure did not reduce the pesticide concentrations in the drainage canals. Neither the introduction of the new regulation nor the improved infrastructure had any significant effect on reducing the contamination of pesticides in water of the Chikugo River. It is probably because most farmers did not properly implement the new requirement of holding paddy water within the field for 7 days after the application of pesticides. Only tightening the regulation would not be sufficient and more actions should be taken to enforce/provide extension support for the new water management regulation in order to reduce the level of residual pesticides in river water in Japan.

Utility of temporal artery biopsy samples for genome-wide analysis of giant cell arteritis

Giant Cell Arteritis (GCA) is the most common vasculitis affecting the elderly. Archived formalin-fixed paraffin-embedded (FFPE) temporal artery biopsy (TAB) specimens potentially represent a valuable resource for large-scale genetic analysis of this disease. FFPE TAB samples were obtained from 12 patients with GCA. Extracted TAB DNA was assessed by real time PCR before restoration using the Illumina HD FFPE Restore Kit. Paired FFPE-blood samples were genotyped on the Illumina OmniExpress FFPE microarray. The FFPE samples that passed stringent quality control measures had a mean genotyping success of >97%. When compared with their matching peripheral blood DNA, the mean discordant heterozygote and homozygote single nucleotide polymorphisms calls were 0.0028 and 0.0003, respectively, which is within the accepted tolerance of reproducibility. This work demonstrates that it is possible to successfully obtain high-quality microarray-based genotypes FFPE TAB samples and that this data is similar to that obtained from peripheral blood.

Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

Partial epilepsy syndrome in a Gypsy family linked to 5q31.3-q32

PURPOSE The restricted genetic diversity and homogeneous molecular basis of Mendelian disorders in isolated founder populations have rarely been explored in epilepsy research. Our long-term goal is to explore the genetic basis of epilepsies in one such population, the Gypsies. The aim of this report is the clinical and genetic characterization of a Gypsy family with a partial epilepsy syndrome. METHODS Clinical information was collected using semistructured interviews with affected subjects and informants. At least one interictal electroencephalography (EEG) recording was performed for each patient and previous data obtained from records. Neuroimaging included structural magnetic resonance imaging (MRI). Linkage and haplotype analysis was performed using the Illumina IVb Linkage Panel, supplemented with highly informative microsatellites in linked regions and Affymetrix SNP 5.0 array data. RESULTS We observed an early-onset partial epilepsy syndrome with seizure semiology strongly suggestive of temporal lobe epilepsy (TLE), with mild intellectual deficit co-occurring in a large proportion of the patients. Psychiatric morbidity was common in the extended pedigree but did not cosegregate with epilepsy. Linkage analysis definitively excluded previously reported loci, and identified a novel locus on 5q31.3-q32 with an logarithm of the odds (LOD) score of 3 corresponding to the expected maximum in this family. DISCUSSION The syndrome can be classified as familial temporal lobe epilepsy (FTLE) or possibly a new syndrome with mild intellectual deficit. The linked 5q region does not contain any ion channel-encoding genes and is thus likely to contribute new knowledge about epilepsy pathogenesis. Identification of the mutation in this family and in additional patients will define the full phenotypic spectrum.

Spatio-temporal modelling of cancer data in Queensland using Bayesian methods

Cancer is the leading contributor to the disease burden in Australia. This thesis develops and applies Bayesian hierarchical models to facilitate an investigation of the spatial and temporal associations for cancer diagnosis and survival among Queenslanders. The key objectives are to document and quantify the importance of spatial inequalities, explore factors influencing these inequalities, and investigate how spatial inequalities change over time. Existing Bayesian hierarchical models are refined, new models and methods developed, and tangible benefits obtained for cancer patients in Queensland. The versatility of using Bayesian models in cancer control are clearly demonstrated through these detailed and comprehensive analyses.

Temporal dependence of in vivo USPIO-enhanced MRI signal changes in human carotid atheromatous plaques

Introduction: Ultrasmall superparamagnetic iron oxide (USPIO)-enhanced MRI has been shown to be a useful modality to image activated macrophages in vivo, which are principally responsible for plaque inflammation. This study determined the optimum imaging time-window to detect maximal signal change post-USPIO infusion using T1-weighted (T1w), T2*- weighted (T2*w) and quantitative T2*(qT 2*) imaging. Methods: Six patients with an asymptomatic carotid stenosis underwent high resolution T1w, T2*w and qT2*MR imaging of their carotid arteries at 1.5 T. Imaging was performed before and at 24, 36, 48, 72 and 96 h after USPIO (Sinerem™, Guerbet, France) infusion. Each slice showing atherosclerotic plaque was manually segmented into quadrants and signal changes in each quadrant were fitted to an exponential power function to model the optimum time for post-infusion imaging. Results: The power function determining the mean time to convergence for all patients was 46, 41 and 39 h for the T1w, T 2*w and qT2*sequences, respectively. When modelling each patient individually, 90% of the maximum signal intensity change was observed at 36 h for three, four and six patients on T1w, T 2*w and qT2*, respectively. The rates of signal change decrease after this period but signal change was still evident up to 96 h. Conclusion: This study showed that a suitable imaging window for T 1w, T2*w and qT2*signal changes post-USPIO infusion was between 36 and 48 h. Logistically, this would be convenient in bringing patients back for one post-contrast MRI, but validation is required in a larger cohort of patients.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.