Three carrier ambiguity resolution : distance-independent performance demonstrated using semi-generated triple frequency GPS signals

In spite of significant research in the development of efficient algorithms for three carrier ambiguity resolution, full performance potential of the additional frequency signals cannot be demonstrated effectively without actual triple frequency data. In addition, all the proposed algorithms showed their difficulties in reliable resolution of the medium-lane and narrow-lane ambiguities in different long-range scenarios. In this contribution, we will investigate the effects of various distance-dependent biases, identifying the tropospheric delay to be the key limitation for long-range three carrier ambiguity resolution. In order to achieve reliable ambiguity resolution in regional networks with the inter-station distances of hundreds of kilometers, a new geometry-free and ionosphere-free model is proposed to fix the integer ambiguities of the medium-lane or narrow-lane observables over just several minutes without distance constraint. Finally, the semi-simulation method is introduced to generate the third frequency signals from dual-frequency GPS data and experimentally demonstrate the research findings of this paper.

Neoproterozoic glacial deposits of the Kimberly Region and northwestern Northern Territory, Australia

Neoproterozoic glacigenic formations are preserved in the Kimberley region and northwestern Northern Territory of northern Australia. They are distributed in the west Kimberley adjacent to the northern margins of the King Leopold Orogen, the Mt Ramsay area at the junction of the King Leopold and Halls Creek Orogens, and the east Kimberley, adjacent to the eastern margin of the Halls Creek Orogen. Small outlier glacigenic deposits are preserved in the Litchfield Province, Northern Territory (Uniya Formation) and Georgina Basin, western Queensland (Little Burke Formation). Glacigenic strata comprise diamictite, conglomerate, sandstone and pebbly mudstone and characterize the Walsh, Landrigan and Fargoo/Moonlight Valley formations. Thin units of laminated dolomite sit conformably at the top of the Walsh, Landrigan and Moonlight Valley formations. Glacigenic units are also interbedded with the carbonate platform deposits of the Egan Formation and Boonall Dolomite. δ13C data are available for all carbonate units. There is no direct chronological constraint on these successions. Dispute over regional correlation of the Neoproterozoic succession has been largely resolved through biostratigraphic, chemostratigraphic and lithostratigraphic analysis. However, palaeomagnetic results from the Walsh Formation are inconsistent with sedimentologically based correlations. Two stratigraphically defined glaciations are preserved in northwestern Australia: the ‘Landrigan Glaciation’, characterized by southwest-directed continental ice-sheet movement and correlated with late Cryogenian glaciation elsewhere in Australia and the world; and, the ‘Egan Glaciation’, a more localized glaciation of the Ediacaran Period. Future research focus should include chronology, palaeomagnetic constraint and tectonostratigraphic controls on deposition.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

Design of fixed order robust power oscillation damper for TCSC

This paper illustrates robust fixed order power oscillation damper design for mitigating power systems oscillations. From implementation and tuning point of view, such low and fixed structure is common practice for most practical applications, including power systems. However, conventional techniques of optimal and robust control theory cannot handle the constraint of fixed-order as it is, in general, impossible to ensure a target closed-loop transfer function by a controller of any given order. This paper deals with the problem of synthesizing or designing a feedback controller of dynamic order for a linear time-invariant plant for a fixed plant, as well as for an uncertain family of plants containing parameter uncertainty, so that stability, robust stability and robust performance are attained. The desired closed-loop specifications considered here are given in terms of a target performance vector representing a desired closed-loop design. The performance of the designed controller is validated through non-linear simulations for a range of contingencies.

Accuracy of rate estimation using relaxed-clock models with a critical focus on the early metazoan radiation

In recent years, a number of phylogenetic methods have been developed for estimating molecular rates and divergence dates under models that relax the molecular clock constraint by allowing rate change throughout the tree. These methods are being used with increasing frequency, but there have been few studies into their accuracy. We tested the accuracy of several relaxed-clock methods (penalized likelihood and Bayesian inference using various models of rate change) using nucleotide sequences simulated on a nine-taxon tree. When the sequences evolved with a constant rate, the methods were able to infer rates accurately, but estimates were more precise when a molecular clock was assumed. When the sequences evolved under a model of autocorrelated rate change, rates were accurately estimated using penalized likelihood and by Bayesian inference using lognormal and exponential models of rate change, while other models did not perform as well. When the sequences evolved under a model of uncorrelated rate change, only Bayesian inference using an exponential rate model performed well. Collectively, the results provide a strong recommendation for using the exponential model of rate change if a conservative approach to divergence time estimation is required. A case study is presented in which we use a simulation-based approach to examine the hypothesis of elevated rates in the Cambrian period, and it is found that these high rate estimates might be an artifact of the rate estimation method. If this bias is present, then the ages of metazoan divergences would be systematically underestimated. The results of this study have implications for studies of molecular rates and divergence dates.

Tinamous and moa flock together : mitochondrial genome sequence analysis reveals independent losses of flight among ratites

Ratites are large, flightless birds and include the ostrich, rheas, kiwi, emu, and cassowaries, along with extinct members, such as moa and elephant birds. Previous phylogenetic analyses of complete mitochondrial genome sequences have reinforced the traditional belief that ratites are monophyletic and tinamous are their sister group. However, in these studies ratite monophyly was enforced in the analyses that modeled rate heterogeneity among variable sites. Relaxing this topological constraint results in strong support for the tinamous (which fly) nesting within ratites. Furthermore, upon reducing base compositional bias and partitioning models of sequence evolution among protein codon positions and RNA structures, the tinamou–moa clade grouped with kiwi, emu, and cassowaries to the exclusion of the successively more divergent rheas and ostrich. These relationships are consistent with recent results from a large nuclear data set, whereas our strongly supported finding of a tinamou–moa grouping further resolves palaeognath phylogeny. We infer flight to have been lost among ratites multiple times in temporally close association with the Cretaceous–Tertiary extinction event. This circumvents requirements for transient microcontinents and island chains to explain discordance between ratite phylogeny and patterns of continental breakup. Ostriches may have dispersed to Africa from Eurasia, putting in question the status of ratites as an iconic Gondwanan relict taxon. [Base composition; flightless; Gondwana; mitochondrial genome; Palaeognathae; phylogeny; ratites.]

A new approach to automatically producing schedules for cane railways

The scheduling of locomotive movements on cane railways has proven to be a very complex task. Various optimisation methods have been used over the years to try and produce an optimised schedule that eliminates or minimises bin supply delays to harvesters and the factory, while minimising the number of locomotives, locomotive shifts and cane bins, and also the cane age. This paper reports on a new attempt to develop an automatic scheduler using a mathematical model solved using mixed integer programming and constraint programming approaches and blocking parallel job shop scheduling fundamentals. The model solution has been explored using conventional constraint programming search techniques and found to produce a reasonable schedule for small-scale problems with up to nine harvesters. While more effort is required to complete the development of the full model with metaheuristic search techniques, the work completed to date gives confidence that the metaheuristic techniques will provide near optimal solutions in reasonable time.

Viruses of banana in East Africa

Bananas are one of the world's most important food crops, providing sustenance and income for millions of people in developing countries and supporting large export industries. Viruses are considered major constraints to banana production, germplasm multiplication and exchange, and to genetic improvement of banana through traditional breeding. In Africa, the two most important virus diseases are bunchy top, caused by Banana bunchy top virus (BBTV), and banana streak disease, caused by Banana streak virus (BSV). BBTV is a serious production constraint in a number of countries within/bordering East Africa, such as Burundi, Democratic Republic of Congo, Malawi, Mozambique, Rwanda and Zambia, but is not present in Kenya, Tanzania and Uganda. Additionally, epidemics of banana streak disease are occurring in Kenya and Uganda. The rapidly growing tissue culture (TC) industry within East Africa, aiming to provide planting material to banana farmers, has stimulated discussion about the need for virus indexing to certify planting material as virus-free. Diagnostic methods for BBTV and BSV have been reported and, for BBTV, PCR-based assays are reliable and relatively straightforward. However for BSV, high levels of serological and genetic variability and the presence of endogenous virus sequences within the banana genome complicate diagnosis. Uganda has been shown to contain the greatest diversity in BSV isolates found anywhere in the world. A broad-spectrum diagnostic test for BSV detection, which can discriminate between endogenous and episomal BSV sequences, is a priority. This PhD project aimed to establish diagnostic methods for banana viruses, with a particular focus on the development of novel methods for BSV detection, and to use these diagnostic methods for the detection and characterisation of banana viruses in East Africa. A novel rolling-circle amplification (RCA) method was developed for the detection of BSV. Using samples of Banana streak MY virus (BSMYV) and Banana streak OL virus (BSOLV) from Australia, this method was shown to distinguish between endogenous and episomal BSV sequences in banana plants. The RCA assay was used to screen a collection of 56 banana samples from south-west Uganda for BSV. RCA detected at least five distinct BSV isolates in these samples, including BSOLV and Banana streak GF virus (BSGFV) as well as three BSV isolates (Banana streak Uganda-I, -L and -M virus) for which only partial sequences had been previously reported. These latter three BSV had only been detected using immuno-capture (IC)-PCR and thus were possible endogenous sequences. In addition to its ability to detect BSV, the RCA protocol was also demonstrated to detect other viruses within the family Caulimoviridae, including Sugar cane bacilliform virus, and Cauliflower mosaic virus. Using the novel RCA method, three distinct BSV isolates from both Kenya and Uganda were identified and characterised. The complete genome of these isolates was sequenced and annotated. All six isolates were shown to have a characteristic badnavirus genome organisation with three open reading frames (ORFs) and the large polyprotein encoded by ORF 3 was shown to contain conserved amino acid motifs for movement, aspartic protease, reverse transcriptase and ribonuclease H activities. As well, several sequences important for expression and replication of the virus genome were identified including the conserved tRNAmet primer binding site present in the intergenic region of all badnaviruses. Based on the International Committee on Taxonomy of Viruses (ICTV) guidelines for species demarcation in the genus Badnavirus, these six isolates were proposed as distinct species, and named Banana streak UA virus (BSUAV), Banana streak UI virus (BSUIV), Banana streak UL virus (BSULV), Banana streak UM virus (BSUMV), Banana streak CA virus (BSCAV) and Banana streak IM virus (BSIMV). Using PCR with species-specific primers designed to each isolate, a genotypically diverse collection of 12 virus-free banana cultivars were tested for the presence of endogenous sequences. For five of the BSV no amplification was observed in any cultivar tested, while for BSIMV, four positive samples were identified in cultivars with a B-genome component. During field visits to Kenya, Tanzania and Uganda, 143 samples were collected and assayed for BSV. PCR using nine sets of species-specific primers, and RCA, were compared for BSV detection. For five BSV species with no known endogenous counterpart (namely BSCAV, BSUAV, BSUIV, BSULV and BSUMV), PCR was used to detect 30 infections from the 143 samples. Using RCA, 96.4% of these samples were considered positive, with one additional sample detected using RCA which was not positive using PCR. For these five BSV, PCR and RCA were both useful for identifying infected samples, irrespective of the host cultivar genotype (Musa A- or B-genome components). For four additional BSV with known endogenous counterparts in the M. balbisiana genome (BSOLV, BSGFV, BSMYV and BSIMV), PCR was shown to detect 75 infections from the 143 samples. In 30 samples from cultivars with an A-only genome component there was 96.3% agreement between PCR positive samples and detection using RCA, again demonstrating either PCR or RCA are suitable methods for detection. However, in 45 samples from cultivars with some B-genome component, the level of agreement between PCR positive samples and RCA positive samples was 70.5%. This suggests that, in cultivars with some B-genome component, many infections were detected using PCR which were the result of amplification of endogenous sequences. In these latter cases, RCA or another method which discriminates between endogenous and episomal sequences, such as immuno-capture PCR, is needed to diagnose episomal BSV infection. Field visits were made to Malawi and Rwanda to collect local isolates of BBTV for validation of a PCR-based diagnostic assay. The presence of BBTV in samples of bananas with bunchy top disease was confirmed in 28 out of 39 samples from Malawi and all nine samples collected in Rwanda, using PCR and RCA. For three isolates, one from Malawi and two from Rwanda, the complete nucleotide sequences were determined and shown to have a similar genome organisation to previously published BBTV isolates. The two isolates from Rwanda had at least 98.1% nucleotide sequence identity between each of the six DNA components, while the similarity between isolates from Rwanda and Malawi was between 96.2% and 99.4% depending on the DNA component. At the amino acid level, similarities in the putative proteins encoded by DNA-R, -S, -M, - C and -N were found to range between 98.8% to 100%. In a phylogenetic analysis, the three East African isolates clustered together within the South Pacific subgroup of BBTV isolates. Nucleotide sequence comparison to isolates of BBTV from outside Africa identified India as the possible origin of East African isolates of BBTV.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Assessment of “change in flexibility method” in structural health monitoring systems

The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.