Fine-tuning of unmanned aerial surveillance for ecological systems

Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.

Computational Techniques for Haplotype Inference and for Local Alignment Significance

This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.

Optimisation Problems in Wireless Sensor Networks : Local Algorithms and Local Graphs

This thesis studies optimisation problems related to modern large-scale distributed systems, such as wireless sensor networks and wireless ad-hoc networks. The concrete tasks that we use as motivating examples are the following: (i) maximising the lifetime of a battery-powered wireless sensor network, (ii) maximising the capacity of a wireless communication network, and (iii) minimising the number of sensors in a surveillance application. A sensor node consumes energy both when it is transmitting or forwarding data, and when it is performing measurements. Hence task (i), lifetime maximisation, can be approached from two different perspectives. First, we can seek for optimal data flows that make the most out of the energy resources available in the network; such optimisation problems are examples of so-called max-min linear programs. Second, we can conserve energy by putting redundant sensors into sleep mode; we arrive at the sleep scheduling problem, in which the objective is to find an optimal schedule that determines when each sensor node is asleep and when it is awake. In a wireless network simultaneous radio transmissions may interfere with each other. Task (ii), capacity maximisation, therefore gives rise to another scheduling problem, the activity scheduling problem, in which the objective is to find a minimum-length conflict-free schedule that satisfies the data transmission requirements of all wireless communication links. Task (iii), minimising the number of sensors, is related to the classical graph problem of finding a minimum dominating set. However, if we are not only interested in detecting an intruder but also locating the intruder, it is not sufficient to solve the dominating set problem; formulations such as minimum-size identifying codes and locating dominating codes are more appropriate. This thesis presents approximation algorithms for each of these optimisation problems, i.e., for max-min linear programs, sleep scheduling, activity scheduling, identifying codes, and locating dominating codes. Two complementary approaches are taken. The main focus is on local algorithms, which are constant-time distributed algorithms. The contributions include local approximation algorithms for max-min linear programs, sleep scheduling, and activity scheduling. In the case of max-min linear programs, tight upper and lower bounds are proved for the best possible approximation ratio that can be achieved by any local algorithm. The second approach is the study of centralised polynomial-time algorithms in local graphs these are geometric graphs whose structure exhibits spatial locality. Among other contributions, it is shown that while identifying codes and locating dominating codes are hard to approximate in general graphs, they admit a polynomial-time approximation scheme in local graphs.

The biology and natural history of Tripogon loliiformis (Poaceae, Chloridoideae), an Australian resurrection grass

Tripogon loliiformis is a desiccation-tolerant grass that occurs throughout mainland Australia. There has been recent interest in this species as a model system for understanding desiccation tolerance in a native grass at the structural, molecular and physiological levels. However, not much is known about the biology and natural history of this species, despite its widespread geographic distribution and remarkable capability of withstanding prolonged drying. We provide an overview of the genus by consolidating information from a wide variety of sources. We report a variety of new and interesting observations on the general biology, ecology and desiccation response of T. loliiformis and conclude by highlighting areas for future research.

From Leffingwell to Spoede : Highlights in the history of Temple Israel.

Brochure, describing the history of the Jewish community in St. Louis, founded mostly by immigrants from Germany.

Lecture by Jacques Judah Lyons on the history of the Jews, given before the Hebrew Religious and Literary Library Association

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Legacies of War--[Ten percent terror]

Ten Percent Terror brings together leading creatives from the fields of contemporary theatre, contemporary dance, music theatre, circus and digital arts in the first collaboration of its kind. Commissioned by Brisbane Powerhouse, with support from the Anzac Centenary Arts and Culture Fund and in partnership with Dancenorth and Company 2, this is an inter-disciplinary work that combines theatrical narrative with eloquent physicality, through circus and dance, to express certain truths of the soldiers' experience. This production will be a circus-narrative that uses the form and language of circus to express the key themes of risk, panic and brotherhood. Ten Percent Terror is intended to be a work of scale, yet also intimacy: of stillness and panic, inertia and chaos. Project partners, Dancenorth and Company 2, share the vision to use contemporary artistic disciplines to connect younger and modern audiences to the ANZAC legacy, perhaps offering a connection for those audiences that they may not find through more traditional art forms. The development process has included a community research project in Townsville, conducted by Shane Pike, which explored contemporary Australians’ stories through interviews with serving military personnel and the local community, as well as collecting photographic documentation and other artefacts from around Townsville. This was followed by an archival research project in Brisbane, where Pike reviewed letters, photographs and personal accounts of soldiers from WW1. The results of these projects will be used by the creative team to inform the development of Ten Percent Terror. Given Townsville’s reputation as Australia’s ‘garrison’ city, the project partners plan to deliver the world premiere performance of Ten Percent Terror in Townsville in late 2015. It is intended that Ten Percent Terror will receive its Brisbane premiere in November 2015 at Brisbane Powerhouse, as part of a four-performance season. This expert panel included discussion of the project and its place in analysing key aspects of Australia's wartime history.

Development of a transient gradient enhanced non local continuum damage mechanics model for masonry

Due to the advent of varied types of masonry systems a comprehensive failure mechanism of masonry essential for the understanding of its behaviour is impossible to be determined from experimental testing. As masonry is predominantly used in wall structures a biaxial stress state dominates its failure mechanism. Biaxial testing will therefore be necessary for each type of masonry, which is expensive and time consuming. A computational method would be advantageous; however masonry is complex to model which requires advanced computational modelling methods. This thesis has formulated a damage mechanics inspired modelling method and has shown that the method effectively determines the failure mechanisms and deformation characteristics of masonry under biaxial states of loading.

Inhibition of Human Two-Pore Domain K+ Channel TREK1 by Local Anesthetic Lidocaine: Negative Cooperativity and Half-of-Sites Saturation Kinetics

TWIK-related K+ channel TREK1, a background leak K+ channel, has been strongly implicated as the target of several general and local anesthetics. Here, using the whole-cell and single-channel patch-clamp technique, we investigated the effect of lidocaine, a local anesthetic, on the human (h) TREK1 channel heterologously expressed in human embryonic kidney 293 cells by an adenoviral-mediated expression system. Lidocaine, at clinical concentrations, produced reversible, concentration-dependent inhibition of hTREK1 current, with IC50 value of 180 mu M, by reducing the single-channel open probability and stabilizing the closed state. We have identified a strategically placed unique aromatic couplet (Tyr352 and Phe355) in the vicinity of the protein kinase A phosphorylation site, Ser348, in the C-terminal domain (CTD) of hTREK1, that is critical for the action of lidocaine. Furthermore, the phosphorylation state of Ser348 was found to have a regulatory role in lidocaine-mediated inhibition of hTREK1. It is interesting that we observed strong intersubunit negative cooperativity (Hill coefficient = 0.49) and half-of-sites saturation binding stoichiometry (half-reaction order) for the binding of lidocaine to hTREK1. Studies with the heterodimer of wild-type (wt)-hTREK1 and Delta 119 C-terminal deletion mutant (hTREK1(wt)-Delta 119) revealed that single CTD of hTREK1 was capable of mediating partial inhibition by lidocaine, but complete inhibition necessitates the cooperative interaction between both the CTDs upon binding of lidocaine. Based on our observations, we propose a model that explains the unique kinetics and provides a plausible paradigm for the inhibitory action of lidocaine on hTREK1.