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.

Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection

Knowledge of the amounts and types of fatty acids in groundnut oil is beneficial, particularly from a nutritional standpoint. Germplasm evaluation data for fatty acid composition on 819 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for eight quantitative fatty acid descriptors have been documented. Statistical assessment, via methods of pattern analysis, summarised and described the patterns of variation in fatty acid composition of the groundnut accessions in the Australian germplasm collection. Presentation of the results from principal components analysis and hierarchical cluster analysis using a biplot was shown to be a very useful interpretative tool. Such a biplot enables a simultaneous examination of the relationships among all the accessions and the fatty acids. Unlike that information available via database searches, the results from contribution analysis together with the biplot provide a global picture of the diversity available for use in plant breeding programs. The use of standardised data for eight fatty acids, compared to using three specific fatty acids, provided a better description of the total diversity available because it remains relevant with possible changes in the nutritional preferences for fatty acids. Fatty acid composition was found to vary in relation to the branching pattern of the accessions. This pattern is generally indicative of the botanical types of groundnuts; Virginia (alternate) compared to Spanish and Valencia (sequential) botanical types.

Pattern analysis of the diversity of morphological plant attributes and herbage yield in a world collection of white clover (Trifolium repens L.) germplasm characterised in a summer moisture stress environment of Australia

Information on the variation available for different plant attributes has enabled germplasm collections to be effectively utilised in plant breeding. A world sourced collection of white clover germplasm has been developed at the White Clover Resource Centre at Glen Innes, New South Wales. This collection of 439 accessions was characterised under field conditions as a preliminary study of the genotypic variation for morphological attributes; stolon density, stolon branching, number of nodes. number of rooted nodes, stolon thickness, internode length, leaf length, plant height and plant spread, together with seasonal herbage yield. Characterisation was conducted on different batches of germplasm (subsets of accessions taken from the complete collection) over a period of five years. Inclusion of two check cultivars, Haifa and Huia, in each batch enabled adjustment of the characterisation data for year effects and attribute-by-year interaction effects. The component of variance for seasonal herbage yield among batches was large relative to that for accessions. Accession-by-experiment and accession-by-season interactions for herbage yield were not detected. Accession mean repeatability for herbage yield across seasons was intermediate (0.453). The components of genotypic variance among accessions for all attributes, except plant height, were larger than their respective standard errors. The estimates of accession mean repeatability for the attributes ranged from low (0.277 for plant height) to intermediate (0.544 for internode length). Multivariate techniques of clustering and ordination were used to investigate the diversity present among the accessions in the collection. Both cluster analysis and principal component analysis suggested that seven groups of accessions existed. It was also proposed from the pattern analysis results that accessions from a group characterised by large leaves, tall plants and thick stolons could be crossed with accessions from a group that had above average stolon density and stolon branching. This material could produce breeding populations to be used in recurrent selection for the development of white clover cultivars for dryland summer moisture stress environments in Australia. The germplasm collection was also found to be deficient in genotypes with high stolon density, high number of branches high number of rooted nodes and large leaves. This warrants addition of new germplasm accessions possessing these characteristics to the present germplasm collection.

1000 voices : an online public collection of life stories

1000 voices is an international web-based platform for gathering and displaying more than 1000 life stories about the lived experience of people with disability. The site contains life stories told by people with disability that are presented in multiple media and formats, including text, audio, video, graphics and visual art...

Data collection techniques

The objective of this chapter is to provide an overview of traffic data collection that can and should be used for the calibration and validation of traffic simulation models. There are big differences in availability of data from different sources. Some types of data such as loop detector data are widely available and used. Some can be measured with additional effort, for example, travel time data from GPS probe vehicles. Some types such as trajectory data are available only in rare situations such as research projects.

Understanding and analyzing a large collection of archived swimming videos

In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.

Amanda Gearing Queensland Flood Collection 2011-2012

A collection of oral history recordings, photographs, hand drawn maps, videos and speech notes relating to the 2011 Queensland floods and the major flood event that occurred in Toowoomba and the Lockyer Valley region on 10 January 2011: a flash flood (described as an 'inland tsunami') which devastatingly took 21 human lives. The collection, amassed by Toowoomba-based journalist Amanda Gearing for her Master of Arts degree, includes 86 oral history recordings of flood survivors and rescuers in Spring Bluff, Murphys Creek, Toowoomba, Withcott, Postmans Ridge, Helidon, Carpendale and Grantham as well as digital photographs and videos taken by a number of those interviewed including those taken by Amanda Gearing and other locals. The interviews are very personal and powerful recollections of the experience of the flood event. Some recall feelings of fear and despair and tell of trauma and loss which continues well after the flood event. All are stories of resilience and hope, of rebuilding lives, of lessons learnt, and recommendations in order to avoid the same devastating results in future disasters.

Improving national hospice/palliative care service symptom outcomes systematically through point-of-care data collection, structured feedback and benchmarking

PURPOSE Every health care sector including hospice/palliative care needs to systematically improve services using patient-defined outcomes. Data from the national Australian Palliative Care Outcomes Collaboration aims to define whether hospice/palliative care patients' outcomes and the consistency of these outcomes have improved in the last 3 years. METHODS Data were analysed by clinical phase (stable, unstable, deteriorating, terminal). Patient-level data included the Symptom Assessment Scale and the Palliative Care Problem Severity Score. Nationally collected point-of-care data were anchored for the period July-December 2008 and subsequently compared to this baseline in six 6-month reporting cycles for all services that submitted data in every time period (n = 30) using individual longitudinal multi-level random coefficient models. RESULTS Data were analysed for 19,747 patients (46 % female; 85 % cancer; 27,928 episodes of care; 65,463 phases). There were significant improvements across all domains (symptom control, family care, psychological and spiritual care) except pain. Simultaneously, the interquartile ranges decreased, jointly indicating that better and more consistent patient outcomes were being achieved. CONCLUSION These are the first national hospice/palliative care symptom control performance data to demonstrate improvements in clinical outcomes at a service level as a result of routine data collection and systematic feedback.

Evaluation of saliva collection devices for the analysis of proteins

Background: Human saliva mirrors the body's health and can be collected non-invasively, does not require specialized skills and is suitable for large population based screening programs. The aims were twofold: to evaluate the suitability of commercially available saliva collection devices for quantifying proteins present in saliva and to provide levels for C-reactive protein (CRP), myoglobin, and immunoglobin E (IgE) in saliva of healthy individuals as a baseline for future studies. Methods: Saliva was collected from healthy volunteers (n = 17, ages 18-33 years). The following collection methods were evaluated: drool; Salimetrics (R) Oral Swab (SOS); Salivette (R) Cotton and Synthetic (Sarstedt) and Greiner Bio-One Saliva Collection System (GBO SCS (R)). We used AlphaLISA (R) assays to measure CRP, IgE and myoglobin levels in human saliva. Results: Significant (p<0.05) differences in the salivary flow rates were observed based on the method of collection, Le. salivary flow rates were significantly lower (p<0.05) in unstimulated saliva (Le. drool and SOS), when compared with mechanically stimulated methods (p<0.05) (Salivette (R) Cotton and Synthetic) and acid stimulated method (p<0.05) (SCS (R)). Saliva collected using SOS yielded significantly (p<0.05) lower concentrations of myoglobin and CRP, whilst, saliva collected using the Salivette (R) Cotton and Synthetic swab yielded significantly (p<0.05) lower myoglobin and IgE concentrations respectively. Conclusions: The results demonstrated significantly relevant differences in analyte levels based on the collection method. Significant differences in the salivary flow rates were also observed depending on the saliva collection method. The data provide preliminary baseline values for salivary CRP, myoglobin, and IgE levels in healthy participants and based on the collection method. (C) 2012 Elsevier B.V. All rights reserved.

Collection and determination of nucleotide metabolites in neonatal and adult saliva by high performance liquid chromatography with tandem mass spectrometry

Saliva contains a number of biochemical components which may be useful for diagnosis/monitoring of metabolic disorders, and as markers of cancer or heart disease. Saliva collection is attractive as a non-invasive sampling method for infants and elderly patients. We present a method suitable for saliva collection from neonates. We have applied this technique for the determination of salivary nucleotide metabolites. Saliva was collected from 10 healthy neonates using washed cotton swabs, and directly from 10 adults. Two methods for saliva extraction from oral swabs were evaluated. The analytes were then separated using high performance liquid chromatography (HPLC) with tandem mass spectrometry (MS/MS). The limits of detection for 14 purine/pyrimidine metabolites were variable, ranging from 0.01 to 1.0 mu M. Recovery of hydrophobic purine/pyrimidine metabolites from cotton tips was consistently high using water/acetonitrile extraction (92.7-111%) compared with water extraction alone. The concentrations of these metabolites were significantly higher in neonatal saliva than in adults. Preliminary ranges for nucleotide metabolites in neonatal and adult saliva are reported. Hypoxanthine and xanthine were grossly raised in neonates (49.3 +/- 25.4; 30.9 +/- 19.5 mu M respectively) compared to adults (4.3 +/- 3.3; 4.6 +/- 4.5 mu M); nucleosides were also markedly raised in neonates. This study focuses on three essential details: contamination of oral swabs during manufacturing and how to overcome this; weighing swabs to accurately measure small saliva volumes; and methods for extracting saliva metabolites of interest from cotton swabs. A method is described for determining nucleotide metabolites using HPLC with photo-diode array or MS/MS. The advantages of utilising saliva are highlighted. Nucleotide metabolites were not simply in equilibrium with plasma, but may be actively secreted into saliva, and this process is more active in neonates than adults. (C) 2013 Elsevier B.V. All rights reserved.

Recruiting, Sampling and Data Collection with Difficult Populations: Clients of Male Sex Workers.

Although there are many potential new insights to be gained through advancing research on the clients of male sex workers, significant social, ethical and methodological challenges to accessing this population exist. This research project case explores our attempts to recruit a population that does not typically form a cohesive or coherent 'community' and often avoids self-identifying to mitigate the stigma attached to buying sex. We used an arms-length recruitment campaign that focussed on directing potential participants to our study website, which could in turn lead them to participate in an anonymous telephone interview. Barriers to reaching male sex-work clients, however, demanded the evolution of our recruitment strategy. New technologies are part of the solution to accessing a hard-to-reach population, but they only work if researchers engage responsively. We also show how we conducted an in-depth interview with a client and discuss the value of using secondary data.

A case study of utilising concept knowledge in a topic specific document collection

The use of ‘topic’ concepts has shown improved search performance, given a query, by bringing together relevant documents which use different terms to describe a higher level concept. In this paper, we propose a method for discovering and utilizing concepts in indexing and search for a domain specific document collection being utilized in industry. This approach differs from others in that we only collect focused concepts to build the concept space and that instead of turning a user’s query into a concept based query, we experiment with different techniques of combining the original query with a concept query. We apply the proposed approach to a real-world document collection and the results show that in this scenario the use of concept knowledge at index and search can improve the relevancy of results.

Clustering and labeling a web scale document collection using Wikipedia clusters

Clustering is an important technique in organising and categorising web scale documents. The main challenges faced in clustering the billions of documents available on the web are the processing power required and the sheer size of the datasets available. More importantly, it is nigh impossible to generate the labels for a general web document collection containing billions of documents and a vast taxonomy of topics. However, document clusters are most commonly evaluated by comparison to a ground truth set of labels for documents. This paper presents a clustering and labeling solution where the Wikipedia is clustered and hundreds of millions of web documents in ClueWeb12 are mapped on to those clusters. This solution is based on the assumption that the Wikipedia contains such a wide range of diverse topics that it represents a small scale web. We found that it was possible to perform the web scale document clustering and labeling process on one desktop computer under a couple of days for the Wikipedia clustering solution containing about 1000 clusters. It takes longer to execute a solution with finer granularity clusters such as 10,000 or 50,000. These results were evaluated using a set of external data.