The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

Isolation of multiple novel paramyxoviruses from pteropid bat urine

Bats have been found to harbor a number of new emerging viruses with zoonotic potential and there has been a great deal of interest in identifying novel bat pathogens to determine risk to human and animal health. Many groups have identified novel viruses in bats by detection of viral nucleic acid, however virus isolation is still a challenge and there are few reports of viral isolates from bats. In recent years, our group has developed optimized procedures for virus isolation from bat urine, including the use of primary bat cells. In previous reports we have described the isolation of Hendra virus, Menangle virus and Cedar virus, in Queensland, Australia. Here, we report the isolation of four additional novel bat paramyxoviruses from urine collected from beneath pteropid bat (flying fox) colonies in Queensland and New South Wales during 2009-2011.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

A Reactive Inverse PN Algorithm for Collision Avoidance among Multiple Unmanned Aerial Vehicles

While performing a mission, multiple Unmanned Aerial Vehicles (UAVs) need to avoid each other to prevent collisions among them. In this paper, we design a collision avoidance algorithm to resolve the conflict among UAVs that are on a collision course while flying to heir respective destinations. The collision avoidance algorithm consist of each UAV that is on a collision course reactively executing a maneuver that will, as in `inverse' Proportional Navigation (PN), increase Line of Sight (LOS) rate between them, resulting in a `pulling out' of collision course. The algorithm is tested for high density traffic scenarios as well as for robustness in the presence of noise.

Studies on Plant Demography: Ranunculus Repens L., R. Bulbosus L. and R. Acris L.: III. A Mathematical Model Incorporating Multiple Modes of Reproduction

This paper presents a comparative population dynamics study of three closely related species of buttercups (Ranunculus repens, R. acris, and R. bulbosus). The study is based on an investigation of the behaviour of the seeds in soil under field conditions and a continuous monitoring of survival and reproduction of some 9000 individual plants over a period of 21/2 years in a coastal grassland in North Wales. The data were analysed with the help of an extension of Leslie's matrix method which makes possible an simultaneous treatment of vegetative and sexual reproduction. It was found that R. repens (a) depends more heavily on vegetative as compared with sexual reproduction, (b) shows indications of negatively density-dependent population regulation, and (c) exhibits little variation in population growth rates from site to site and from one year to the next. In contrast, R. bulbosus (a) depends exclusively on sexual reproduction, (b) shows indications of a positively density-dependent population behaviour, and (c) exhibits great variation in population growth rates from site to site and from one year to the next. R. acris exhibits an intermediate behaviour in all these respects. It is suggested that the attributes of R. repens are those expected of a species inhabiting a stable environment, while R. bulbosus exhibits some of the characteristics of a fugitive species.

Studies of multiple ionization in the RF spark and vacuum vibrator arc ion sources

Relative abundance distributions of multiply-charged ionic species have been measured for the RF spark and vacuum vibrator are ion sources, for a number of elements. An attempt has been made to explain the observed charge state distribution on the basis of models for the arc and spark plasma. The difficulties in the way of explaining the observed charge state distributions, using the LTE model with Saha distribution as well as the corona model, are pointed out. The distribution can be explained by a diffusion-dominated plasma model with known or calculated values for ionization cross-sections, the single impact model being suitable for the RF spark and the multiple impact model for the vibrator arc.

Dancing practices from multiple perspectives: the increasingly complex role of the contemporary dancer

This paper will discuss the complexities of the role of contemporary dancer in this current epoch, with a particular focus on the multiple identities dancers embody within dance practice and how these accumulate to form a creative self-in-process or ‘moving identity’. Wider issues, such as training will be explored questioning how technical skills can be imparted alongside autonomous learning approaches to ensure that dancers are prepared to negotiate the entrepreneurial ecology of various dance sectors. Furthermore, the paper will examine the shifting relationship between choreographer and dancer from hierarchical to co-creative including how, in spite of the often collaborative nature of dance creation, the marketplace continues to celebrate the singular authorial position of the choreographer. Each of these elements will reflect back the complex issues of agency and creative self-hood that dancers must negotiate in an increasingly diverse and changeable arts environment.

Multiple roles of transfer prices: One vs. two books

This paper investigates multiple roles of transfer prices for shipments of goods and services between entities of a multinational enterprise. At the center is the role of transfer pricing (TP) in tax manipulation, but other roles having to do with internal operations or strategic delegation, etc. are also considered. The interesting question is to what extent and how the different roles of TPs interfere with each other. The answer depends on whether companies use one or two books, i.e. whether they (can) apply different TPs for different purposes. We illustrate, in a stylized model, the competing aims of tax manipulation and strategic delegation. Finally, we briefly look at selected reform proposals, concluding that either TP problems are not addressed, or else new distortions will be introduced instead.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Invertebrate predation and trophic cascades in a pelagic food web : The multiple roles of Chaoborus flavicans (Meigen) in a clay-turbid lake

In lake ecosystems, both fish and invertebrate predators have dramatic effects on their prey communities. Fish predation selects large cladocerans while invertebrate predators prefer prey of smaller size. Since invertebrate predators are the preferred food items for fish, their occurrence at high densities is often connected with the absence or low number of fish. It is generally believed that invertebrate predators can play a significant role only if the density of planktivorous fish is low. However, in eutrophic clay-turbid Lake Hiidenvesi (southern Finland), a dense population of predatory Chaoborus flavicans larvae coexists with an abundant fish population. The population covers the stratifying area of the lake and attains a maximum population density of 23000 ind. m-2. This thesis aims to clarify the effects of Chaoborus flavicans on the zooplankton community and the environmental factors facilitating the coexistence of fish and invertebrate predators. In the stratifying area of Lake Hiidenvesi, the seasonal succession of cladocerans was exceptional. The spring biomass peak of cladocerans was missing and the highest biomass occurred in midsummer. In early summer, the consumption rate by chaoborids clearly exceeded the production rate of cladocerans and each year the biomass peak of cladocerans coincided with the minimum chaoborid density. In contrast, consumption by fish was very low and each study year cladocerans attained maximum biomass simultaneously with the highest consumption by smelt (Osmerus eperlanus). The results indicated that Chaoborus flavicans was the main predator of cladocerans in the stratifying area of Lake Hiidenvesi. The clay turbidity strongly contributed to the coexistence of chaoborids and smelt at high densities. Turbidity exceeding 30 NTU combined with light intensity below 0.1 μE m-2 s-1provides an efficient daytime refuge for chaoborids, but turbidity alone is not an adequate refuge unless combined with low light intensity. In the non-stratifying shallow basins of Lake Hiidenvesi, light intensity exceeds this level during summer days at the bottom of the lake, preventing Chaoborus forming a dense population in the shallow parts of the lake. Chaoborus can be successful particularly in deep, clay-turbid lakes where they can remain high in the water column close to their epilimnetic prey. Suspended clay alters the trophic interactions by weakening the link between fish and Chaoborus, which in turn strengthens the effect of Chaoborus predation on crustacean zooplankton. Since food web management largely relies on manipulations of fish stocks and the cascading effects of such actions, the validity of the method in deep clay-turbid lakes may be questioned.