Australian National University

About: Australian National University is a education organization based out in Canberra, Australian Capital Territory, Australia. It is known for research contribution in the topics: Population & Galaxy. The organization has 34419 authors who have published 109261 publications receiving 4315448 citations. The organization is also known as: The Australian National University & ANU.

Cross-species amplification of soybean (Glycine max) simple sequence repeats (SSRs) within the genus and other legume genera: implications for the transferability of SSRs in plants.

Abstract: We investigated the transferability of 31 soybean (Glycine max) simple sequence repeat (SSR) loci to wild congeners and to other legume genera. Up to 65% of the soybean primer pairs amplified SSRs within Glycine, but frequently, the SSRs were short and interrupted compared with those of soybeans. Nevertheless, 85% of the loci were polymorphic within G. clandestina. Cross-species amplification outside of the genus was much lower (3%-13%), with polymorphism restricted to one primer pair, AG81. AG81 amplified loci in Glycine, Kennedia, and Vigna (Phaseoleae), Vicia (Vicieae), Trifolium (Trifolieae), and Lupinus (Genisteae) within the Papilionoideae, and in Albizia within the Mimosoideae. The primer conservation at AG81 may be explained by its apparent proximity to the seryl-tRNA synthetase gene. Interspecific differences in allele size at AG81 loci reflected repeat length variation within the SSR region and indels in the flanking region. Alleles of identical size with different underlying sequences (size homoplasy) were observed. Our findings and the emerging patterns in other plant studies suggest that in contrast to animals, successful cross-species amplification of SSRs in plants is largely restricted to congeners or closely related genera. Because mutations in both the SSR region and the flanking region contribute to variation in allele size among species, knowledge of DNA sequence is essential before SSR loci can be meaningfully used to address applied and evolutionary questions.

Pedestrian Alignment Network for Large-scale Person Re-Identification

Abstract: Person re-identification (re-ID) is mostly viewed as an image retrieval problem. This task aims to search a query person in a large image pool. In practice, person re-ID usually adopts automatic detectors to obtain cropped pedestrian images. However, this process suffers from two types of detector errors: excessive background and part missing. Both errors deteriorate the quality of pedestrian alignment and may compromise pedestrian matching due to the position and scale variances. To address the misalignment problem, we propose that alignment be learned from an identification procedure. We introduce the pedestrian alignment network (PAN) which allows discriminative embedding learning pedestrian alignment without extra annotations. We observe that when the convolutional neural network learns to discriminate between different identities, the learned feature maps usually exhibit strong activations on the human body rather than the background. The proposed network thus takes advantage of this attention mechanism to adaptively locate and align pedestrians within a bounding box. Visual examples show that pedestrians are better aligned with PAN. Experiments on three large-scale re-ID datasets confirm that PAN improves the discriminative ability of the feature embeddings and yields competitive accuracy with the state-of-the-art methods.

The multi-agent rendezvous problem

Abstract: This paper is concerned with the collective behavior of a group of n > 1 mobile autonomous agents, labelled 1 through n, which can all move in the plane. Each agent is able to continuously track the positions of all other agents currently within its "sensing region" where by an agent's sensing region is meant a closed disk of positive radius r centered at the agent's current position. The multi-agent rendezvous problem is to devise "local" control strategies, one for each agent, which without any active communication between agents, cause all members of the group to eventually rendezvous at single unspecified location. This paper describes two types of strategies for solving the problem. The first consists of agent strategies, which are mutually synchronized, in the sense that all depend on a common clock. The second consists of strategies, which can be implemented independent of each other, without reference to a common clock.

How much variance can be explained by ecologists and evolutionary biologists

Abstract: The average amount of variance explained by the main factor of interest in ecological and evolutionary studies is an important quantity because it allows evaluation of the general strength of research findings. It also has important implications for the planning of studies. Theoretically we should be able to explain 100% of the variance in data, but randomness and noise may reduce this amount considerably in biological studies. We performed a meta-analysis using data from 43 published meta-analyses in ecology and evolution with 93 estimates of mean effect size using Pearson's r and 136 estimates using Hedges' d or g. This revealed that (depending on the exact analysis) the mean amount of variance (r 2) explained was 2.51–5.42%. The various 95% confidence intervals fell between 1.99 and 7.05%. There was a strongly positive relationship between the fail-safe number (the number of null results needed to nullify an effect) and the coefficient of determination (r 2) or effect size. Analysis at the level of individual tests of null hypotheses showed that the amount of variance key factors explained differed among fields with the largest amount in physiological ecology, lower amounts in ecology and the lowest in evolutionary studies. In all fields though, the hypothesized relationship (e.g. main effect of a fixed treatment) explained little of the variation in the trait of interest. Our finding has important implications for the interpretation of scientific studies. Across studies, the average effect size reported is between Pearson r=0.180 and 0.193 and Hedges' d=0.631 and 0.721. Thus the average sample sizes needed to conclude that a particular relationship is absent with a power of 80% and α=0.05 (two-tailed) are considerably larger than usually recorded in studies of evolution and ecology. For example, to detect r=0.193, the required sample size is 207.

Recent reversal in loss of global terrestrial biomass

Abstract: Vegetation change is a key component of the carbon cycle, but quantifying these changes is challenging. Research using passive microwave observations now provides global estimates for forest and non-forest biomass trends over the past two decades.