The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection I. Two-way quantitative data

Data associated with germplasm collections are typically large and multivariate with a considerable number of descriptors measured on each of many accessions. Pattern analysis methods of clustering and ordination have been identified as techniques for statistically evaluating the available diversity in germplasm data. While used in many studies, the approaches have not dealt explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions). To consider the application of these techniques to germplasm evaluation data, 11328 accessions of groundnut (Arachis hypogaea L) from the International Research Institute for the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the rainy and post-rainy growing seasons were used. The ordination technique of principal component analysis was used to reduce the dimensionality of the germplasm data. The identification of phenotypically similar groups of accessions within large scale data via the computationally intensive hierarchical clustering techniques was not feasible and non-hierarchical techniques had to be used. Finite mixture models that maximise the likelihood of an accession belonging to a cluster were used to cluster the accessions in this collection. The patterns of response for the different growing seasons were found to be highly correlated. However, in relating the results to passport and other characterisation and evaluation descriptors, the observed patterns did not appear to be related to taxonomy or any other well known characteristics of groundnut.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Taxonomic resolution and quantification of freshwater macroinvertebrate samples from an Australian dryland river : The benefits and costs of using species abundance data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Twitter data analytics – or : the pleasures and perils of studying Twitter

It might still sound strange to dedicate an entire journal issue exclusively to a single internet platform. But it is not the company Twitter Inc. that draws our attention; this issue is not about a platform and its features and services. It is about its users and the ways in which they interact with one another via the platform, about the situations that motivate people to share their thoughts publicly, using Twitter as a means to reach out to one another. And it is about the digital traces people leave behind when interacting with Twitter, and most of all about the ways in which these traces – as a new type of research data – can also enable new types of research questions and insights.

Reproductive Health as a Human Right: A Matter of Access or Provision?

This article seeks to understand why, despite over three decades of claiming women's reproductive health as a human right, we have seen little progress in reducing their health inequalities and poor health outcomes. I argue that one reason for this lack of progress may be due to a failure to clearly articulate the responsibilities of key actors, crucially states, in ensuring that women have access to, and provision of, services required to realize their reproductive rights. What is needed, this article suggests, is a framework that can translate decades of rights language into action and specifically identify the provisions required to address women's health.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Qualitative spatial reasoning about directions in a corridor containing a single turn

An experiment was conducted to investigate the process of reasoning about directions in an egocentric space. Each participant walked through a corridor containing an angular turn ranging in size from 0° to 90°, in 15° increments. A direction was given to participants at the entrance of the corridor and they were asked to answer this direction at the end of this corridor. Considering the fact that participants had to reason the direction in the featureless corridor, two hypotheses were proposed: (i) reasoning about directions falls into qualitative reasoning by using a small number of coarse angular categories (four 90° categories or eight 45° categories: 90° categories consist of front, back, left, right; 45° categories consist of 90° categories and the four intermediates) that reference axes generate; (ii) reasoning about directions would be done by recalling the rotation angle from the traveling direction to the direction that participants tried to answer. In addition, the configuration of reference axes that participants employed was examined. Both hypotheses were supported, and the data designated that reference axes consisted of eight directions: a pair of orthogonal axes and diagonals.

Metaphors of big data

Metaphors are a common instrument of human cognition, activated when seeking to make sense of novel and abstract phenomena. In this article we assess some of the values and assumptions encoded in the framing of the term big data, drawing on the framework of conceptual metaphor. We first discuss the terms data and big data and the meanings historically attached to them by different usage communities and then proceed with a discourse analysis of Internet news items about big data. We conclude by characterizing two recurrent framings of the concept: as a natural force to be controlled and as a resource to be consumed.

A biomechanical analysis of growing rods used in the management of early onset scoliosis

INTRODUCTION Managing spinal deformities in young children is challenging, particularly early onset scoliosis (EOS). Surgical intervention is often required if EOS has been unresponsive to conservative treatment particularly with rapidly progressive curves. An emerging treatment option for EOS is fusionless scoliosis surgery. Similar to bracing, this surgical option potentially harnesses growth, motion and function of the spine along with correcting spinal deformity. Dual growing rods are one such fusionless treatment, which aims to modulate growth of the vertebrae. The aim of this study was to ascertain the extent to which semiconstrained growing rods (Medtronic, Sofamor, Danek, Memphis, TN) with a telescopic sleeve component, reduce rotational constraint on the spine compared with standard "constrained / rigid" rods and hence potentially provide a more physiological mechanical environment for the growing spine. METHODS Six 40-60kg English Large White porcine spines served as a model for the paediatric human spine. Each spine was dissected into a 7 level thoracolumbar multi-segment unit (MSU), removing all non-ligamentous soft tissues and leaving 3cm of ribs either side. Pure nondestructive axial rotation moments of ±4Nm at a constant rotation rate of 8deg.s-1 were applied to the mounted MSU spines using a biaxial Instron testing machine. Displacement of each vertebral level was captured using a 3D motion tracking system (Optotrak 3020, Northern Digital Inc, Waterloo, ON). Each spine was tested in an un-instrumented state first and then with appropriately sized semi-constrained growing rods and rigid rods in alternating sequence. The rods were secured by multi-axial pedicle screws (Medtronic CD Horizon) at levels 2 and 6 of the construct. The range of motion (ROM), neutral zone (NZ) size and stiffness (Nm.deg-1) were calculated from the Instron load-displacement data and intervertebral ROM was calculated through a MATLAB algorithm from Optotrak data. RESULTS Irrespective of the order of testing, rigid rods significantly reduced the total ROM compared with semi-constrained rods (p<0.05) with in a significantly stiffer spine for both left and right axial rotation (p<0.05). Analysing the intervertebral motion within the instrumented levels 2-6, rigid rods showed reduced ROM compared with semi-constrained growing rods and compared with un-instrumented motion segments. CONCLUSION Semi-constrained growing rods maintain similar stiffness in axial rotation to un-instrumented spines, while dual rigid rods significantly reduce axial rotation. Clinically the effect of semi-constrained growing rods as observed in this study is that they would be expected to allow growth via the telescopic rod components while maintaining the axial flexibility of the spine, which may reduce occurrence of the crankshaft phenomenon.

The stabilising role of the costovertebral joints and spinous processes on thoracic spine stability

Introduction The importance of in vitro biomechanical testing in today’s understanding of spinal pathology and treatment modalities cannot be stressed enough. Different studies have used differing levels of dissection of their spinal segments for their testing protocols[1, 2]. The aim of this study was to assess the impact of removing the costovertebral joints and partial resection of the spinous process sequentially, on the stiffness of the immature thoracic bovine spinal segment. Materials and Methods Thoracic spines from 6-8 week old calves were used. Each spine was dissected and divided into motion segments with 5cm of attached rib on each side and full spinous processes including levels T4-T11 (n=28). They were potted in polymethylemethacrylate. An Instron Biaxial materials testing machine with a custom made jig was used for testing. The segments were tested in flexion/extension, lateral bending and axial rotation at 37⁰C and 100% humidity, using moment control to a maximum 1.75 Nm with a loading rate of 0.3 Nm per second. They were first tested intact for ten load cycles with data collected from the tenth cycle. Progressive dissection was performed by removing first the attached ribs, followed by the spinous process at its base. Biomechanical testing was carried out after each level of dissection using the same protocol. Statistical analysis of the data was performed using repeated measures ANOVA. Results In combined flexion/extension there was a significant reduction in stiffness of 16% (p=0.002). This was mainly after resection of the ribs (14%, p=0.024) and mainly occurred in flexion where stiffness reduced by 22% (p=0.021). In extension, stiffness dropped by 13% (p=0.133). However there was no further significant change in stiffness on resection of the spinous process (<1%) (p=1.00). In lateral bending there was a significant decrease in stiffness of 13% (p<0.001). This comprised a drop of 11% on resection of the ribs (p=0.009) and a further 8% on resection of the spinous process (p=0.014). There was no difference between left and right bending. In axial rotation there was no significant change in stiffness after each stage of dissection (p=0.253). There was no difference between left and right rotation. Conclusion The costovertebral joints play a significant role in providing stability to the bovine thoracic spine in both flexion/extension and lateral bending, whereas the spinous processes play a minor role. Both elements have little effect on axial rotation stability.

Monitoring spatiotemporal dynamics of human movement based on MAC address data

This thesis was a step forward in extracting valuable features from human's movement behaviour in terms of space utilisation based on Media-Access-Control data. This research offered a low-cost and less computational complexity approach compared to existing human's movement tracking methods. This research was successfully applied in QUT's Gardens Point campus and can be scaled to bigger environments and societies. Extractable information from human's movement by this approach can add a significant value to studying human's movement behaviour, enhancing future urban and interior design, improving crowd safety and evacuation plans.

Measuring the biases in self-reported disability status : Evidence from aggregate data

Self-reported health status measures are generally used to analyse Social Security Disability Insurance's (SSDI) application and award decisions as well as the relationship between its generosity and labour force participation. Due to endogeneity and measurement error, the use of self-reported health and disability indicators as explanatory variables in economic models is problematic. We employ county-level aggregate data, instrumental variables and spatial econometric techniques to analyse the determinants of variation in SSDI rates and explicitly account for the endogeneity and measurement error of the self-reported disability measure. Two surprising results are found. First, it is shown that measurement error is the dominating source of the bias and that the main source of measurement error is sampling error. Second, results suggest that there may be synergies for applying for SSDI when the disabled population is larger. © 2011 Taylor & Francis.