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.

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.

Governance Systems Analysis (GSA) : a framework for reforming governance systems

Most commentators understand that contemporary social, economic and environmental challenges require quality governance from global to local scales. While public scrutiny of governance has increased in recent years, the literature on frameworks and methods for analysis in complex, poly-centric and multi-thematic governance systems remains fragmented; displaying many disciplinary or sectoral biases. This paper establishes a stronger theory-based foundation for the analysis of complex governance systems. It also develops a clear analytical framework applicable across a vast array of differing governance themes, domains and scales (GSA). The key methodological steps and evaluative criteria for the GSA framework are determined and practical guidance for its application in reform is provided.

Enhancing Research Productivity of TEFL Academic in China : A Mixed Method Study

As research has become an important indicator of TEFL academics’ overall performance in Chinese higher education institutions, it is critical that TEFL academics are able to meet the expectation of conducting research. This mixed-method study (an initial survey followed by a qualitative collective case study)investigated research productivity of Chinese TEFL academics and associated influences, with the ultimate objective of constructing a framework to help build their research capacity in the future. The findings from this study revealed that the 182 Chinese TEFL academics’ research productivity during 2004-2008 was relatively low. Four influences were identified that impacted on thier research productivity: TEFL disciplinary influences, institutional and departmental research environments, individual characteristics desirable for research, and TEFL academics’ perceptions about research. Drawing upon the above findings, a Framework towards Enhancing Chinese TEFL Academics’ Research Productivity (FECTARP) was constructed. The FECTAR presented a framework for Chinese institutions and TEFL departments to enhance their TEFL academics' research capacity.

Vertical graphene gas- and bio-sensors via catalyst-free, reactive plasma reforming of natural honey

A rapid reforming of natural honey exposed to reactive low-temperature Ar + H2 plasmas produced high-quality, ultra-thin vertical graphenes, without any metal catalyst or external heating. This transformation is only possible in the plasma and fails in similar thermal processes. The process is energy-efficient, environmentally benign, and is much cheaper than common synthesis methods based on purified hydrocarbon precursors. The graphenes retain the essential minerals of natural honey, feature reactive open edges and reliable gas- and bio-sensing performance.

Responses of Swietenia macrophylla (King) seedlings to different sizes of canopy openings in mixed mahogany plantations

A study was conducted during 1997-99 at 2 sites in Sri Lanka (Rambukkana and Kurunegala) to investigate the responses of Swietenia macrophylla seedlings to wide, moderate and narrow openings of high to low shade conditions in a mature mixed mahogany plantations. Survival, stem growth and shoot phenology of seedlings were recorded monthly. Seedling survival a year after planting showed high mortality under high shaded gap (3-8% photosynthetically active radiation (PAR)). At 51 weeks after planting, final stem height and root collar diameter were highly significant under low shaded gaps. Increased number of shoots and shoot lenghts were observed under low shade (50-78% PAR). Increased flushing was seen in all shade regimes during the rainy period. This study illustrates that low shaded gap openings favour seeding survival, stem and shoot growth, and number of shoots. On the contrary, high shaded gaps reduce the growth of seedlings and therefore may be less attractive to shoot borers.

Reforming the procurement of construction and financing of Australian infrastructure : advancing capacity, competition and investment

Funded by an Australian Research Council (ARC) Linkage grant over four years (2009–13), the Major Infrastructure Procurement project sought to find more effective and efficient ways of procuring and delivering the nation’s social and economic infrastructure by investigating constraints relating to construction capacity, competition, and finance in new public sector major infrastructure.1 The research team comprised researchers in construction economics and finance from Queensland University of Technology (QUT), Griffith University (GU), The University of Hong Kong (UHK), and The University of Newcastle (UoN). Project partners included state government departments and agencies responsible for infrastructure procurement and delivery from all Australian mainland states, and private sector companies and peak bodies in the infrastructure sector (see “Introduction” for complete list). There are a number of major outcomes from this research project. The first of these is a scientifically developed decisionmaking model for procurement of infrastructure that deploys a novel and state-of-the-art integration of dominant microeconomic theory (including theories developed by two Nobel Prize winners). The model has been established through empirical testing and substantial experiential evidence as a valid and reliable guide to configuring procurement of new major and mega infrastructure projects in pursuance of superior Valuefor- Money (VfM). The model specifically addresses issues of project size, bundling of contracts, and exchange relationships. In so doing, the model determines the suitability of adopting a Public-Private Partnership (PPP) mode.

Metabolic response to a mixed meal in obese and lean women from two South African populations

Objective Lower lipid and insulin levels are found during a glucose-tolerance test in obese black than obese white South African women. Therefore, β-cell function and lipid metabolism were compared in these populations during a mixed meal. Research Methods and Procedures Blood concentrations of glucose, free fatty acids (FFAs), insulin, lipograms, and in vivo FFA oxidation were determined at fasting and for 7 hours after oral administration of a mixed emulsion containing glucose-casein-sucrose-lipid and [1-13C] palmitic acid in 8 lean black women (LBW), 10 obese black women (OBW), 9 lean white women (LWW), and 10 obese white women (OWW). Subcutaneous and visceral fat mass was assessed by computerized tomography. Results Visceral fat area was higher in OWW (152.7 ± 17.0 cm2) than OBW (80.0 ± 6.7 cm2; p < 0.01). In OBW, 30-minute insulin levels were higher (604.3 ± 117.6 pM) than OWW (311.0 ± 42.9 pM; p < 0.05). Total triglyceride was higher in OWW (706.7 ± 96.0 mM × 7 hours) than OBW (465.7 ± 48.2 mM × 7 hours; p < 0.05) and correlated with visceral fat area (β = 0.38, p = 0.05). Palmitate oxidation was higher in lean than obese women in both ethnic groups and correlated negatively with fat mass (β = −0.58, p < 0.005). Discussion The higher 30-minute insulin response in OBW may reflect a higher insulinotropic effect of FFAs or glucose. The elevated triglyceride level of OWW may be due to their higher visceral fat mass and possibly reduced clearance by adipose tissue.

Organisational culture, leadership behaviour and job satisfaction among primary health care professionals in Saudi Arabia : a mixed-methods study

The purpose of this study was to improve individual and organisational performance in primary health care (PHC) by identifying the relationship between organisational culture, leadership behaviour and job satisfaction. The study used a sequential explanatory mixed methods design, to investigate the relationships between organisational culture, leadership behaviour, and job satisfaction among 550 PHCC professionals in Saudi Arabia. From surveying the PHC professionals, the results highlighted the importance of human caring qualities, including praise and recognition, consideration, and support, with respect to their perceptions of job satisfaction, leadership behaviour, and organisational culture. As a consequence a management framework was proposed to address these issues.

Complementary surface-enhanced resonance raman spectroscopic biodetection of mixed protein solutions by chitosan- and silica-coated plasmon-tuned silver nanoparticles

Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.

Wood density : a tool to find complementary species for the design of mixed species plantations

The successful establishment and growth of mixed-species forest plantations requires that complementary or facilitatory species be identified. This can be difficult in many tropical areas because the growth characteristics of endemic species are often unknown, particularly when grown at potentially higher densities in plantations than in natural forests. Here, we investigate whether wood density is a useful and readily accessible trait for choosing complementary species for mixed species plantations. Wood density represents the carbon investment per unit volume of stem with a trade-off generally found between fast (low wood density) and slow (high wood density) growing species. To do this, we use data collected from 18 highly diverse mixed species plantations (4–23 mostly native species) aged from 6 to 11 years at the time of data collection located on Leyte Island, Philippines. We found significant negative correlations between wood densities and the height of the most abundant species, as well as with measures of overall stand growth and tree diameter size distribution. Not only do species with denser woods have slower growth rates, but also mixed-species plantations with higher average wood density and higher stem density were also less productive, at least in these young plantations. Similarly, stands with a high diversity in wood densities were less productive. There is growing interest in making greater use of native multi-species mixtures in smallholder and community planting programs in the tropics, and our results show databases of wood density values may help improve their design. In the early development stages of plantations, canopy closure and rapid height growth are usually key silvicultural targets, and wood density values can predict the rapid height development of species. If plantations are being grown for the livelihood of small landholders then the best target is to choose some species with different wood densities. This allows an early harvest of low-wood density species for early income, and will also reduce competition for slower growing trees with higher wood densities for later income generation.

Using qualitative mixed methods to study small health care organizations while maximising trustworthiness and authenticity

Background The primary health care sector delivers the majority of health care in western countries through small, community-based organizations. However, research into these healthcare organizations is limited by the time constraints and pressure facing them, and the concern by staff that research is peripheral to their work. We developed Q-RARA—Qualitative Rapid Appraisal, Rigorous Analysis—to study small, primary health care organizations in a way that is efficient, acceptable to participants and methodologically rigorous. Methods Q-RARA comprises a site visit, semi-structured interviews, structured and unstructured observations, photographs, floor plans, and social scanning data. Data were collected over the course of one day per site and the qualitative analysis was integrated and iterative. Results We found Q-RARA to be acceptable to participants and effective in collecting data on organizational function in multiple sites without disrupting the practice, while maintaining a balance between speed and trustworthiness. Conclusions The Q-RARA approach is capable of providing a richly textured, rigorous understanding of the processes of the primary care practice while also allowing researchers to develop an organizational perspective. For these reasons the approach is recommended for use in small-scale organizations both within and outside the primary health care sector.