Using textual analysis with Concept Inventories to identify root causes of misconceptions

Engineers must have deep and accurate conceptual understanding of their field and Concept inventories (CIs) are one method of assessing conceptual understanding and providing formative feedback. Current CI tests use Multiple Choice Questions (MCQ) to identify misconceptions and have undergone reliability and validity testing to assess conceptual understanding. However, they do not readily provide the diagnostic information about students’ reasoning and therefore do not effectively point to specific actions that can be taken to improve student learning. We piloted the textual component of our diagnostic CI on electrical engineering students using items from the signals and systems CI. We then analysed the textual responses using automated lexical analysis software to test the effectiveness of these types of software and interviewed the students regarding their experience using the textual component. Results from the automated text analysis revealed that students held both incorrect and correct ideas for certain conceptual areas and provided indications of student misconceptions. User feedback also revealed that the inclusion of the textual component is helpful to students in assessing and reflecting on their own understanding.

Global, regional, and national age–sex specifi c all-cause and cause-specifi c mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0–65·6) in 1990, to 71·5 years (UI 71·0–71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8–48·2) to 54·9 million (UI 53·6–56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25–39 years and older than 75 years and for men aged 20–49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.

The root locus method: application to linear stability analysis and design of cooperative car-following models

A global framework for linear stability analyses of traffic models, based on the dispersion relation root locus method, is presented and is applied taking the example of a broad class of car-following (CF) models. This approach is able to analyse all aspects of the dynamics: long waves and short wave behaviours, phase velocities and stability features. The methodology is applied to investigate the potential benefits of connected vehicles, i.e. V2V communication enabling a vehicle to send and receive information to and from surrounding vehicles. We choose to focus on the design of the coefficients of cooperation which weights the information from downstream vehicles. The coefficients tuning is performed and different ways of implementing an efficient cooperative strategy are discussed. Hence, this paper brings design methods in order to obtain robust stability of traffic models, with application on cooperative CF models

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Genetic analysis of resistance to root-lesion nematode (Pratylenchus thornei) in wheat

The inheritance of resistance to root-lesion nematode was investigated in five synthetic hexaploid wheat lines and two bread wheat lines using a half-diallel design of F1 and F2 crosses. The combining ability of resistance genes in the synthetic hexaploid wheat lines was compared with the performance of the bread wheat line 'GS50a', the source of resistance to Pratylenchus thornei used in Australian wheat breeding programmes. Replicated glasshouse trials identified P. thornei resistance as polygenic and additive in gene action. General combining ability (GCA) of the parents was more important than specific combining ability (SCA) effects in the inheritance of P. thornei resistance in both F1 and F2 populations. The synthetic hexaploid wheat line 'CPI133872' was identified as the best general combiner, however, all five synthetic hexaploid wheat lines possessed better GCA than 'GS50a'. The synthetic hexaploid wheat lines contain novel sources of P. thornei resistance that will provide alternative and more effective sources of resistance to be utilized in wheat breeding programmes

Identification of quantitative trait loci for resistance to two species of root-lesion nematode (Pratylenchus thornei and P. neglectus) in wheat

Pratylenchus thornei and P. neglectus are two species of root-lesion nematode that cause substantial yield losses in wheat. No commercially available wheat variety has resistance to both species. A doubled-haploid population developed from a cross between the synthetic hexaploid wheat line CPI133872 and the bread wheat Janz was used to locate and tag quantitative trait loci (QTLs) associated with resistance to both P. thornei and P. neglectus. Wheat plants were inoculated with both species of nematode in independent replicated glasshouse trials repeated over 2 years. Known locations of wheat microsatellite markers were used to construct a framework map. After an initial single-marker analysis to detect marker-trait linkages, chromosome regions associated with putative QTLs were targetted with microsatellite markers to increase map density in the chromosome regions of interest. In total, 148 wheat microsatellite markers and 21 amplified fragment length polymorphism markers were mapped. The codominant microsatellite marker Xbarc183 on the distal end of chromosome 6DS was allelic for resistance to both P. thornei and P. neglectus. The QTL were designated QRlnt.lrc-6D.1 and QRlnn.lrc-6D.1, for the 2 traits, respectively. The allele inherited from CPI133872 explained 22.0-24.2% of the phenotypic variation for P. thornei resistance, and the allele inherited from Janz accounted for 11.3-14.0% of the phenotypic variation for P. neglectus resistance. Composite interval mapping identified markers that flank a second major QTL on chromosome 6DL (QRlnt.lrc-6D.2) that explained 8.3-13.4% of the phenotypic variation for P. thornei resistance. An additional major QTL associated with P. neglectus resistance was detected on chromosome 4DS (QRlnn.lrc-4D.1) and explained a further 10.3-15.4% of the phenotypic variation. The identification and tagging of nematode resistance genes with molecular markers will allow appropriate allele combinations to be selected, which will aid the successful breeding of wheat with dual nematode resistance.

Resistance to the root-lesion nematode Pratylenchus thornei of Iranian landrace wheat.

Pratylenchus thornei is widespread throughout the wheat-growing regions in Australia and overseas and can cause yield losses of up to 70% in some intolerant cultivars. The most effective forms of management of P. thornei populations are crop rotation and plant breeding. There have been no wheat accessions identified as completely resistant to P. thornei, therefore breeding programs have used moderately resistant parents. The objective of the present research was to evaluate 274 Iranian landrace wheats for resistance to P. thornei and identify accessions with resistance superior to the current best resistance source (GS50a). Plants were grown in P. thornei inoculated soil under controlled conditions in a glasshouse pot experiment for 16 weeks. Ninety-two accessions found to be resistant or moderately so were retested in a second experiment. From combined analysis of these experiments, 34 accessions were identified as resistant with reproduction factors (final population per kg soil/initial inoculum rate per kg soil) <= 1. In total, 25 accessions were more resistant than GS50a, with AUS28470 significantly (P < 0.05) more resistant. The resistant Iranian landraces identified in the present study are a valuable untapped genetic pool offering improved levels of P. thornei resistance over current parents in Australian wheat-breeding programs.

GM solutions to root diseases of cereals - A situation analysis and business case

Root disease causes about $503 million in losses annually to Australia's wheat and barley industries. Because of these large losses and in many cases the difficulty in reducing these losses through breeding or management, root diseases are candidates for solutions through genetic modification (GM). Through an extensive review of the scientific literature and patents, a range of approaches to GM solutions to root diseases are critically discussed. Given the high cost of regulatory approval for GM crops and a complex intellectual property (IP) landscape, it is likely that research in this area will be done in collaboration with international partners.

Highly heritable resistance to root-lesion nematode (Pratylenchus thornei) in Australian chickpea germplasm observed using an optimised glasshouse method and multi-environment trial analysis

Pratylenchus thornei is a root-lesion nematode (RLN) of economic significance in the grain growing regions of Australia. Chickpea (Cicer arietinum) is a significant legume crop grown throughout these regions, but previous testing found most cultivars were susceptible to P. thornei. Therefore, improved resistance to P. thornei is an important objective of the Australian chickpea breeding program. A glasshouse method was developed to assess resistance of chickpea lines to P. thornei, which requires relatively low labour and resource input, and hence is suited to routine adoption within a breeding program. Using this method, good differentiation of chickpea cultivars for P. thornei resistance was measured after 12 weeks. Nematode multiplication was higher for all genotypes than the unplanted control, but of the 47 cultivars and breeding lines tested, 17 exhibited partial resistance, allowing less than two fold multiplication. The relative differences in resistance identified using this method were highly heritable (0.69) and were validated against P. thornei data from seven field trials using a multi-environment trial analysis. Genetic correlations for cultivar resistance between the glasshouse and six of the field trials were high (>0.73). These results demonstrate that resistance to P. thornei in chickpea is highly heritable and can be effectively selected in a limited set of environments. The improved resistance found in a number of the newer chickpea cultivars tested shows that some advances have been made in the P. thornei resistance of Australian chickpea cultivars, and that further targeted breeding and selection should provide incremental improvements.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

Root system traits of Norway spruce, Scots pine, and silver birch in mixed boreal forests: an analysis of root architecture, morphology, and anatomy

The aim of this thesis was to unravel the functional-structural characteristics of root systems of Betula pendula Roth., Picea abies (L.) Karst., and Pinus sylvestris L. in mixed boreal forest stands differing in their developmental stage and site fertility. The root systems of these species had similar structural regularities: horizontally-oriented shallow roots defined the horizontal area of influence, and within this area, each species placed fine roots in the uppermost soil layers, while sinker roots defined the maximum rooting depth. Large radial spread and high ramification of coarse roots, and the high specific root length (SRL) and root length density (RLD) of fine roots indicated the high belowground competitiveness and root plasticity of B. pendula. Smaller radial root spread and sparser branching of coarse roots, and low SRL and RLD of fine roots of the conifers could indicate their more conservative resource use and high association with and dependence on ectomycorrhiza-forming fungi. The vertical fine root distributions of the species were mostly overlapping, implying the possibility for intense belowground competition for nutrients. In each species, conduits tapered and their frequency increased from distal roots to the stem, from the stem to the branches, and to leaf petioles in B. pendula. Conduit tapering was organ-specific in each species violating the assumptions of the general vascular scaling model (WBE). This reflects the hierarchical organization of a tree and differences between organs in the relative importance of transport, safety, and mechanical demands. The applied root model was capable of depicting the mass, length and spread of coarse roots of B. pendula and P. abies, and to the lesser extent in P. sylvestris. The roots did not follow self-similar fractal branching, because the parameter values varied within the root systems. Model parameters indicate differences in rooting behavior, and therefore different ecophysiological adaptations between species.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

Transboundary diagnostic analysis. Vol. 1. Issues, proximate and root causes

The Transboundary Diagnostic Analysis(TDA) quantifies and ranks water-related environmental transboundary issues and their causes according to the severity of environmental and/or socio-economic impacts. The three main issues in BOBLME are; overexploitation of marine living resources; degradation of mangroves, coral reefs and seagrasses; pollution and water quality. Volume 1 describes the transboundary issues in BOBLME and their proximate and underlying root causes. These will be used to develop a Strategic Action Plan (SAP)

Analysis of the estrogenic components in kudzu root by bioassay and high performance liquid chromatography

The estrogenic activity of the Chinese herb kudzu root was investigated by a recombinant yeast screening assay (YES). Isoflavones are the main components in the plant, of which puerarin is the most abundant one. The kudzu root extract was separated into four fractions according to the polarity. The crude extract and its sub-fractions, except the water fraction, showed clear estrogenic activity and the potencies were in the range of 10(-3) to 10(-1) g/l. The ligand potency was used to compare the estrogenic activity of these fractions. The crude extract and its sub-fractions were further analyzed by high performance liquid chromatography (HPLC) to correlate the activity and the active components. Bioassay and chemical analysis showed that theoretical estrogenic activity expressed as equivalent 17 beta-estradiol concentration or the cumulative effects are comparable to that experimentally determined by YES. The results showed that the high content of isoflavones as well as the high estrogenic activity could make kudzu root extract an interesting candidate for hormone replacement therapy. (c) 2005 Elsevier Ltd. All rights reserved.