LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.

A recurrent mutation in the BMP type I receptor ACVR1 causes inherited and sporadic fibrodysplasia ossificans progressiva

Fibrodysplasia ossificans progressiva (FOP) is a rare autosomal dominant disorder of skeletal malformations and progressive extraskeletal ossification. We mapped FOP to chromosome 2q23-24 by linkage analysis and identified an identical heterozygous mutation (617G→A; R206H) in the glycine-serine (GS) activation domain of ACVR1, a BMP type I receptor, in all affected individuals examined. Protein modeling predicts destabilization of the GS domain, consistent with constitutive activation of ACVR1 as the underlying cause of the ectopic chondrogenesis, osteogenesis and joint fusions seen in FOP.

Australian data do not support current pharmaceutical benefits scheme criteria for use of tumour necrosis factor-α inhibitors in ankylosing spondylitis

On the basis of local data, we write in support of the conclusions of Smith and Ahern that current Pharmaceu- tical Benefits Scheme (PBS) criteria for tumour necrosis factor (TNF)-a inhibitors in ankylosing spondylitis (AS) are not evidence-based. 1 As a prerequisite to the appropriate use of biological therapy in AS, three aspects of the disease need to be defined: (i) diagnosis, (ii) activity and (iii) therapeutic failure (Table 1)....

QUT’s research data storage solutions: A launchpad for research journeys

This poster presents key features of how QUT’s integrated research data storage and management services work with researchers through their own individual or team research life cycle. By understanding the characteristics of research data, and the long-term need to store this data, QUT has provided resources and tools that support QUT’s goal of being a research intensive institute. Key to successful delivery and operation has been the focus upon researchers’ individual needs and the collaboration between providers, in particular, Information Technology Services, High Performance Computing and Research Support, and QUT Library. QUT’s Research Data Storage service provides all QUT researchers (staff and Higher Degree Research students (HDRs)) with a secure data repository throughout the research data lifecycle. Three distinct storage areas provide for raw research data to be acquired, project data to be worked on, and published data to be archived. Since the service was launched in late 2014, it has provided research project teams from all QUT faculties with acquisition, working or archival data space. Feedback indicates that the storage suits the unique needs of researchers and their data. As part of the workflow to establish storage space for researchers, Research Support Specialists and Research Data Librarians consult with researchers and HDRs to identify data storage requirements for projects and individual researchers, and to select and implement the most suitable data storage services and facilities. While research can be a journey into the unknown[1], a plan can help navigate through the uncertainty. Intertwined in the storage provision is QUT’s Research Data Management Planning tool. Launched in March 2015, it has already attracted 273 QUT staff and 352 HDR student registrations, and over 620 plans have been created (2/10/2015). Developed in collaboration with Office of Research Ethics and Integrity (OREI), uptake of the plan has exceeded expectations.

The effect of transforming growth factor β1 gene polymorphisms in ankylosing spondylitis

Objectives. To determine whether genetic polymorphisms in or near the transforming growth factor β1 (TGFB1) locus were associated d with susceptibility to or severity of ankylosing spondylitis (AS). Methods. Five intragenic single-nucleotide polymorphisms (SNP) and three microsatellite markers flanking the TGFB1 locus were genotyped. Seven hundred and sixty-two individuals from 184 multiplex families were genotyped for the microsatellite markers and two of the promoter SNPs. One thousand and two individuals from 212 English and 170 Finnish families with AS were genotyped for all five intragenic SNPs. A structured questionnaire was used to assess the age of symptom onset, disease duration and disease severity scores, including the BASDAI (Bath Ankylosing Spondylitis Disease Activity Index) and BASFI (Bath Ankylosing Spondylitis Functional Index). Results. A weak association was noted between the rare TGFB1 + 1632 T allele and AS in the Finnish population (P = 0.04) and in the combined data set (P = 0.03). No association was noted between any other SNPs or SNP haplotype and AS, even among those families with positive non-parametric linkage scores. The TGFB1 +1632 polymorphism was also associated with a younger age of symptom onset (English population, allele 2 associated with age of onset greater by 4.2 yr, P = 0.05; combined data set, allele 2 associated with age of onset greater by 3.2 yr, P = 0.02). A haplotype of coding region SNPs (TGFB1 +869/ +915+1632 alleles 2/1/2) was associated with age of symptom onset in both the English parent-case trios and the combined data set (English data set, haplotype 2/1/2 associated with age of onset greater by 4.9 yr, P = 0.03; combined data set, haplotype 2/1/2 associated with greater age of onset by 4.2 yr, P = 0.006). Weak linkage with AS susceptibility was noted and the peak LOD score was 1.3 at distance 2 cM centromeric to the TGFB1 gene. No other linkage or association was found between quantitative traits and the markers. Conclusion. This study suggests that the polymorphisms within the TGFB1 gene play at most a small role in AS and that other genes encoded on chromosome 19 are involved in susceptibility to the disease.

Genetic control of bone density and turnover: Role of the collagen 1α1, estrogen receptor, and vitamin D receptor genes

Genetic factors are known to influence both the peak bone mass and probably the rate of change in bone density. A range of regulatory and structural genes has been proposed to be involved including collagen 1α1 (COL1A1), the estrogen receptor (ER), and the vitamin D receptor (VDR), but the actual genes involved are uncertain. We therefore studied the role of the COL1A1 and VDR loci in control of bone density by linkage in 45 dizygotic twin pairs and 29 nuclear families comprising 120 individuals. The influences on bone density of polymorphisms of COL1A1, VDR, and ER were studied by association both cross-sectionally and longitudinally in 193 elderly postmenopausal women (average age, 69 years) over a mean follow-up time of 6.3 years. Weak linkage of the COL1A1 locus with bone density was observed in both twins and families (p = 0.02 in both data sets), confirming previous observations of linkage of this locus with bone density. Association between the MscI polymorphism of COL1A1 and rate of lumbar spine bone loss was observed with significant gene-environment interaction related to dietary calcium intake (p = 0.0006). In the lowest tertile of dietary calcium intake, carriers of "s" alleles lost more bone than "SS" homozygotes (p = 0.01), whereas the opposite was observed in the highest dietary calcium intake (p = 0.003). Association also was observed between rate of bone loss at both the femoral neck and the lumbar spine and the TaqI VDR polymorphism (p = 0.03). This association was strongest in those in the lowest tertile of calcium intake, also suggesting the presence of gene-environment interaction involving dietary calcium and VDR, influencing bone turnover. No significant association was observed between the PvuII ER polymorphism alone or in combination with VDR or COL1A1 genotypes, with either bone density or its rate of change. These data support the involvement of COL1A1 in determination of bone density and the interaction of both COL1A1 and VDR with calcium intake in regulation of change of bone density over time.

Suggestive linkage of the parathyroid receptor type 1 to osteoporosis

We have investigated the role of 23 candidate genes in the control of bone mineral density (BMD) by linkage studies in families of probands with osteoporosis (lumbar spine [LS] or femoral neck [FN] BMD T score < -2.5) and low BMD relative to an age- and gender-matched cohort (Z score < -2.0). One hundred and fifteen probands (35 male, 80 female) and 499 of their first- or second-degree relatives (223 males and 276 females) were recruited for the study. BMD was measured at the LS and FN using dual-energy X-ray absorptiometry and expressed as age- and gender-matched Z scores corrected for body mass index. The candidate genes studied were the androgen receptor, type I collagen A1 (COLIA1), COLIA2, COLIIA1, vitamin D receptor (VDR), colony-stimulating factor 1, calcium-sensing receptor, epidermal growth factor (EGF), estrogen receptor 1 (ESR1), fibrillin type 1, insulin-like growth factor 1, interleukin-1 alpha (IL-1α), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-11 (IL-11), osteopontin, parathyroid hormone (PTH), PTH-related peptide, PTH receptor type 1 (PTHR1), transforming growth factor-beta 1, and tumor necrosis factors alpha and beta. Sixty-four microsatellites lying close to or within these genes were investigated for linkage with BMD. Using the program MapMaker/Sibs there was suggestive evidence of linkage between BMD and PTHR1 (maximum LOD score obtained [MLS] 2.7-3.5). Moderate evidence of linkage was also observed with EGF (MLS 1.8), COLIA1 (MLS 1.7), COLIIA1/VDR (MLS 1.7), ESR1 (MLS 1.4), IL-1α (MLS 1.4), IL-4 (MLS 1.2), and IL-6 (MLS 1.2). Variance components analysis using the program ACT, correcting for proband-wise ascertainment, also showed evidence of linkage (p ≤0.05) at markers close to or within the candidate genes IL- 1α, PTHR1, IL-6, and COLIIA1/VDR. Further studies will be required to confirm these findings, to refine the location of gene responsible for the observed linkage, and to screen the candidate genes targeted at these loci for mutations.

Computer-assisted sampling of acoustic data for more efficient determination of bird species richness

Bird species richness survey is one of the most intriguing ecological topics for evaluating environmental health. Here, bird species richness denotes the number of unique bird species in a particular area. Factors affecting the investigation of bird species richness include weather, observation bias, and most importantly, the prohibitive costs of conducting surveys at large spatiotemporal scales. Thanks to advances in recording techniques, these problems have been alleviated by deploying sensors for acoustic data collection. Although automated detection techniques have been introduced to identify various bird species, the innate complexity of bird vocalizations, the background noise present in the recording and the escalating volumes of acoustic data pose a challenging task on determination of bird species richness. In this paper we proposed a two-step computer-assisted sampling approach for determining bird species richness in one-day acoustic data. First, a classification model is built based on acoustic indices for filtering out minutes that contain few bird species. Then the classified bird minutes are ordered by an acoustic index and the redundant temporal minutes are removed from the ranked minute sequence. The experimental results show that our method is more efficient in directing experts for determination of bird species compared with the previous methods.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.

Constrained Linear Spectral Unmixing Technique for Regional Land Cover Mapping Using MODIS Data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up-to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat-TM/ETM+, IRS-ICID LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 in), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end-members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications. Index Terms-Remote sensing, digital

An analysis of MONTBLEX data on heat and momentum flux at Jodhpur

Parameterization of sensible heat and momentum fluxes as inferred from an analysis of tower observations archived during MONTBLEX-90 at Jodhpur is proposed, both in terms of standard exchange coefficients C-H and C-D respectively and also according to free convection scaling. Both coefficients increase rapidly at low winds (the latter more strongly) and with increasing instability. All the sensible heat flux data at Jodhpur (wind speed at 10m <(U)over bar (10)>, < 8ms(-1)) also obey free convection scaling, with the flux proportional to the '4/3' power of an appropriate temperature difference such as that between 1 and 30 m. Furthermore, for <(U)over bar (10)> < 4 ms(-1) the momentum flux displays a linear dependence on wind speed.

The case for “n«all”: Why the Big Data revolution will probably happen differently in the mining sector

Big Data and predictive analytics have received significant attention from the media and academic literature throughout the past few years, and it is likely that these emerging technologies will materially impact the mining sector. This short communication argues, however, that these technological forces will probably unfold differently in the mining industry than they have in many other sectors because of significant differences in the marginal cost of data capture and storage. To this end, we offer a brief overview of what Big Data and predictive analytics are, and explain how they are bringing about changes in a broad range of sectors. We discuss the “N=all” approach to data collection being promoted by many consultants and technology vendors in the marketplace but, by considering the economic and technical realities of data acquisition and storage, we then explain why a “n « all” data collection strategy probably makes more sense for the mining sector. Finally, towards shaping the industry’s policies with regards to technology-related investments in this area, we conclude by putting forward a conceptual model for leveraging Big Data tools and analytical techniques that is a more appropriate fit for the mining sector.

Constructing a traditional Chinese medicine data warehouse application

The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.

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.