'A programmable digital signal averager' Reply

In a recent paper, Srinivasan et al (1980) have described a programmable digital signal averager with facility for programming the sampling period, number of channels and number of sweeps. We have examined this paper in some detail and find that some points need clarification.

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

Key message “To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.” Abstract Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

Formal description, compression and transformation of digital pictures II. Picture algebra and geometry

In an earlier paper (Part I) we described the construction of Hermite code for multiple grey-level pictures using the concepts of vector spaces over Galois Fields. In this paper a new algebra is worked out for Hermite codes to devise algorithms for various transformations such as translation, reflection, rotation, expansion and replication of the original picture. Also other operations such as concatenation, complementation, superposition, Jordan-sum and selective segmentation are considered. It is shown that the Hermite code of a picture is very powerful and serves as a mathematical signature of the picture. The Hermite code will have extensive applications in picture processing, pattern recognition and artificial intelligence.

Formal description, compression and transformation of digital pictures

This paper describes the application of vector spaces over Galois fields, for obtaining a formal description of a picture in the form of a very compact, non-redundant, unique syntactic code. Two different methods of encoding are described. Both these methods consist in identifying the given picture as a matrix (called picture matrix) over a finite field. In the first method, the eigenvalues and eigenvectors of this matrix are obtained. The eigenvector expansion theorem is then used to reconstruct the original matrix. If several of the eigenvalues happen to be zero this scheme results in a considerable compression. In the second method, the picture matrix is reduced to a primitive diagonal form (Hermite canonical form) by elementary row and column transformations. These sequences of elementary transformations constitute a unique and unambiguous syntactic code-called Hermite code—for reconstructing the picture from the primitive diagonal matrix. A good compression of the picture results, if the rank of the matrix is considerably lower than its order. An important aspect of this code is that it preserves the neighbourhood relations in the picture and the primitive remains invariant under translation, rotation, reflection, enlargement and replication. It is also possible to derive the codes for these transformed pictures from the Hermite code of the original picture by simple algebraic manipulation. This code will find extensive applications in picture compression, storage, retrieval, transmission and in designing pattern recognition and artificial intelligence systems.

Understanding the barriers to the implementation of precision agriculture in the central region

There is an increasing requirement for more astute land resource management through efficiencies in agricultural inputs in a sugar cane production system. A precision agriculture (PA) approach can provide a pathway for a sustainable sugarcane production system. One of the impediments to the adoption of PA practices is access to paddock-scale mapping layers displaying variability in soil properties, crop growth and surface drainage. Variable rate application (VRA) of nutrients is an important component of PA. However, agronomic expertise within PA systems has fallen well behind significant advances in PA technologies. Generally, advisers in the sugar industry have a poor comprehension of the complex interaction of variables that contribute to within-paddock variations in crop growth. This is regarded as a significant impediment to the progression of PA in sugarcane and is one of the reasons for the poor adoption of VRA of nutrients in a PA approach to improved sugar cane production. This project therefore has established a number of key objectives which will contribute to the adoption of PA and the staged progression of VRA supported by relevant and practical agronomic expertise. These objectives include provision of base soils attribute mapping that can be determined using Veris 3100 Electrical Conductivity (EC) and digital elevation datasets using GPS mapping technology for a large sector of the central cane growing region using analysis of archived satellite imagery to determine the location and stability of yield patterns over time and in varying seasonal conditions on selected project study sites. They also include the stablishment of experiments to determine appropriate VRA nitrogen rates on various soil types subjected to extended anaerobic conditions, and the establishment of trials to determine nitrogen rates applicable to a declining yield potential associated with the aging of ratoons in the crop cycle. Preliminary analysis of archived yield estimation data indicates that yield patterns remain relatively stable overtime. Results also indicate the where there is considerable variability in EC values there is also significant variation in yield.

Who am I? Developing pre-service teacher identity in a digital world

The notions of identity and teacher education have attracted considerable research over the years, revealing a strong correlation between teacher beliefs and practices and the resultant impact on pedagogical practices in the classroom. In an era where the use of digital technologies should be synonymous with teacher pedagogical practices and transforming education, there is a growing need for pre-service teachers to develop an identity that resonates with pedagogical practices that engage and connect with students in a positive and productive way. With many educational institutions also mandating that educators use digital technologies as a tool to support and enhance teaching, pre-service teacher education needs to ensure that students understand and develop a positive identity within this digital world. Current literature acknowledges that many educators adopt digital technologies in the classroom without sometimes fully understanding its scope or impact. It is within this context that this paper reports on a three-year study of first year pre-service education students and their understanding of identity in a digital world. More specifically, the study identifies how students currently use social and digital media in their personal and professional lives to identify themselves online in order to promote a positive image. The study also seeks to identify how these technologies and an understanding of identity can be utilised to promote a positive first year experience.

Deeply superficial digital media engagement? The case of Twitter and Movember 2013

Using activity generated with Twitter during Movember 2013, we interrogate the natures of superficiality running through what can be defined as a highly successful public health engagement intervention. Indeed, Movember arguably has not just been successful in one year in terms of raising funds for the causes it is concerned with, it has done this year-on-year since 2004. We tracked the keyword 'movember' (without the hash symbol) using an in-house installation of YourTwapperkeeper hosted on a NECTAR server. Data collection ran from 01 October - 04 December 2013, covering the ramp-up and wind-down periods of the event. We collected a total of 1,313,426 tweets from 759,345 unique users.

Fine mapping of qGW1, a major QTL for grain weight in sorghum

Key message We detected seven QTLs for 100-grain weight in sorghum using an F 2 population, and delimited qGW1 to a 101-kb region on the short arm of chromosome 1, which contained 13 putative genes. Abstract Sorghum is one of the most important cereal crops. Breeding high-yielding sorghum varieties will have a profound impact on global food security. Grain weight is an important component of grain yield. It is a quantitative trait controlled by multiple quantitative trait loci (QTLs); however, the genetic basis of grain weight in sorghum is not well understood. In the present study, using an F2 population derived from a cross between the grain sorghum variety SA2313 (Sorghum bicolor) and the Sudan-grass variety Hiro-1 (S. bicolor), we detected seven QTLs for 100-grain weight. One of them, qGW1, was detected consistently over 2 years and contributed between 20 and 40 % of the phenotypic variation across multiple genetic backgrounds. Using extreme recombinants from a fine-mapping F3 population, we delimited qGW1 to a 101-kb region on the short arm of chromosome 1, containing 13 predicted gene models, one of which was found to be under purifying selection during domestication. However, none of the grain size candidate genes shared sequence similarity with previously cloned grain weight-related genes from rice. This study will facilitate isolation of the gene underlying qGW1 and advance our understanding of the regulatory mechanisms of grain weight. SSR markers linked to the qGW1 locus can be used for improving sorghum grain yield through marker-assisted selection.

Mapping the carriage of flaA-restriction fragment length polymorphism Campylobacter genotypes on poultry carcasses through the processing chain and comparison to clinical isolates

Poultry are considered a major source for campylobacteriosis in humans. A total of 1866 Campylobacter spp. isolates collected through the poultry processing chain were typed using flaA-restriction fragment length polymorphism to measure the impact of processing on the genotypes present. Temporally related human clinical isolates (n = 497) were also typed. Isolates were obtained from whole chicken carcass rinses of chickens collected before scalding, after scalding, before immersion chilling, after immersion chilling and after packaging as well as from individual caecal samples. A total of 32 genotypes comprising at least four isolates each were recognised. Simpson's Index of Diversity (D) was calculated for each sampling site within each flock, for each flock as a whole and for the clinical isolates. From caecal collection to after packaging samples the D value did not change in two flocks, decreased in one flock and increased in the fourth flock. Dominant genotypes occurred in each flock but their constitutive percentages changed through processing. There were 23 overlapping genotypes between clinical and chicken isolates. The diversity of Campylobacter is flock dependant and may alter through processing. This study confirms that poultry are a source of campylobacteriosis in the Australian population although other sources may contribute.

Making the most of spatial information in health: A tutorial in Bayesian disease mapping for areal data

Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health and other fields, policy or decision makers, health geographers, spatial analysts, public health professionals, and epidemiologists.