Bayesian Modelling of Direct and Indirect Effects of Marine Reserves on Fishes : A thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University, Albany, New Zealand.

This thesis reviews and develops modern advanced statistical methodology for sampling and modelling count data from marine ecological studies, with specific applications to quantifying potential direct and indirect effects of marine reserves on fishes in north eastern New Zealand. Counts of snapper (Pagrus auratus: Sparidae) from baited underwater video surveys from an unbalanced, multi-year, hierarchical sampling programme were analysed using a Bayesian Generalised Linear Mixed Model (GLMM) approach, which allowed the integer counts to be explicitly modelled while incorporating multiple fixed and random effects. Overdispersion was modelled using a zero-inflated negative-binomial error distribution. A parsimonious method for zero inflation was developed, where the mean of the count distribution is explicitly linked to the probability of an excess zero. Comparisons of variance components identified marine reserve status as the greatest source of variation in counts of snapper above the legal size limit. Relative densities inside reserves were, on average, 13-times greater than outside reserves. Small benthic reef fishes inside and outside the same three reserves were surveyed to evaluate evidence for potential indirect effects of marine reserves via restored populations of fishery-targeted predators such as snapper. Sites for sampling were obtained randomly from populations of interest using spatial data and geo-referencing tools in R—a rarely used approach that is recommended here more generally to improve field-based ecological surveys. Resultant multispecies count data were analysed with multivariate GLMMs implemented in the R package MCMCglmm, based on a multivariate Poisson lognormal error distribution. Posterior distributions for hypothesised effects of interest were calculated directly for each species. While reserves did not appear to affect densities of small fishes, reserve-habitat interactions indicated that some endemic species of triplefin (Tripterygiidae) had different associations with small-scale habitat gradients inside vs outside reserves. These patterns were consistent with a behavioural risk effect, where small fishes may be more strongly attracted to refuge habitats to avoid predators inside vs outside reserves. The approaches developed and implemented in this thesis respond to some of the major current statistical and logistic challenges inherent in the analysis of counts of organisms. This work provides useful exemplar pathways for rigorous study design, modelling and inference in ecological systems

A matrix perturbation view of the small world phenomenon

We use techniques from applied matrix analysis to study small world cutoff in a Markov chain. Our model consists of a periodic random walk plus uniform jumps. This has a direct interpretation as a teleporting random walk, of the type used by search engines to locate web pages, on a simple ring network. More loosely, the model may be regarded as an analogue of the original small world network of Watts and Strogatz [Nature, 393 (1998), pp. 440-442]. We measure the small world property by expressing the mean hitting time, averaged over all states, in terms of the expected number of shortcuts per random walk. This average mean hitting time is equivalent to the expected number of steps between a pair of states chosen uniformly at random. The analysis involves nonstandard matrix perturbation theory and the results come with rigorous and sharp asymptotic error estimates. Although developed in a different context, the resulting cutoff diagram agrees closely with that arising from the mean-field network theory of Newman, Moore, and Watts [Phys. Rev. Lett., 84 (2000), pp. 3201-3204]

Renewable Energy Electricity Generation in Arizona: What, Why, and Maybe How: Working Paper Series--02-35

Traditional fossil fuel production of electricity has serious externality issues that influence air quality, public health and viewscapes. In order to limit these influences, public policy aims at increasing the production of electricity using renewable fuels. For a variety of reasons, including market cost barriers, antiquated government policy and the overall lack of knowledge by energy consumers, renewable energy has had a tough time finding a niche in the energy marketplace in Arizona. In this paper we explain the problems with fossil fuel and nuclear energy sources, discuss the possibilities for renewable energy sources, digress on the theoretical question of treating air quality as a private externality or a public good, and propose various policy implements that will allow the state of Arizona to become a leader in the production of electricity from renewable sources

Laser-only adaptive optics achieves significant image quality gains compared to seeing-limited observations over the entire sky

Adaptive optics laser guide star systems perform atmospheric correction of stellar wavefronts in two parts: stellar tip-tilt and high-spatial-order laser-correction. The requirement of a sufficiently bright guide star in the field-of-view to correct tip-tilt limits sky coverage. Here we show an improvement to effective seeing without the need for nearby bright stars, enabling full sky coverage by performing only laser-assisted wavefront correction. We used Robo-AO, the first robotic AO system, to comprehensively demonstrate this laser-only correction. We analyze observations from four years of efficient robotic operation covering 15,000 targets and 42,000 observations, each realizing different seeing conditions. Using an autoguider (or a post-processing software equivalent) and the laser to improve effective seeing independent of the brightness of a target, Robo-AO observations show a 39+/-19% improvement to effective FWHM, without any tip-tilt correction. We also demonstrate that 50% encircled-energy performance without tip-tilt correction remains comparable to diffraction-limited, standard Robo-AO performance. Faint-target science programs primarily limited by 50% encircled-energy (e.g. those employing integral field spectrographs placed behind the AO system) may see significant benefits to sky coverage from employing laser-only AO.Comment: Accepted for publication in The Astronomical Journal. 7 pages, 6 figure

Learning Models for Following Natural Language Directions in Unknown Environments

Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. Recent advancements have given rise to robots that are able to interpret natural language manipulation and navigation commands, but these methods require a prior map of the robot's environment. In this paper, we propose a novel learning framework that enables robots to successfully follow natural language route directions without any previous knowledge of the environment. The algorithm utilizes spatial and semantic information that the human conveys through the command to learn a distribution over the metric and semantic properties of spatially extended environments. Our method uses this distribution in place of the latent world model and interprets the natural language instruction as a distribution over the intended behavior. A novel belief space planner reasons directly over the map and behavior distributions to solve for a policy using imitation learning. We evaluate our framework on a voice-commandable wheelchair. The results demonstrate that by learning and performing inference over a latent environment model, the algorithm is able to successfully follow natural language route directions within novel, extended environments.Comment: ICRA 201

Can Multimedia Learning Tools Enhance Creative Thinking?

The increasing demand for creativity in all domains of study has made this unique construct a surviving means for individuals (Amabile, 1998) and organizations (Dhillon, 2006) which prompts the effort to prioritize creativity development and research particularly in the educational context. Moreover, technological advancement has blessed educational practitioners with the emergence of new teaching and learning tools and approaches. Transforming static learning materials into multimedia forms is an advantage of the technology which has been proven to be effective in enhancing learners' knowledge construction and understanding (Mayer, 2009). The question is whether multimedia learning tools (MLT) could further help learners in their cognitive process and think creatively. Hence, two studies were conducted to test the impact of MLT on mechanical engineering students' creative thinking. MLT on a specific subject were designed and developed, and used by the students at an engineering-based university in Malaysia. The first experiment was a one-group pretest-posttest non-randomized design involving 27 students, and the second experiment was a quasi-experimental two-group pretest posttest non-randomized design involving 64 students. The exposure to the MLT was the treatment condition. Participants' creative thinking was measured using the Torrance Tests of Creative Thinking (TTCT), Verbal forms. Paired-samples t-test results of the first experiment showed significant differences in all elements of students' creative thinking. The results of the TTCT for the second experiment were analyzed using ANCOVA and simple linear regression. The ANCOVA results did not yield significant results. However, the regression analysis was able to predict that the variation in the creative thinking tests was higher when participants were exposed to the MLT. Most responses from the students' interviews also indicated that the MLT have positively influenced their creative thinking. Therefore, this study has shown that there is positive impact on mechanical engineering students' creative thinking when they are exposed to the use of MLT

Synthetic metabolons for metabolic engineering.

Journal ArticleResearch Support, Non-U.S. Gov'tReviewThis is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of Experimental Botany following peer review. The definitive publisher-authenticated version J. Exp. Bot. (2014) 65 (8) pp. 1947-1954 is available online at: http://jxb.oxfordjournals.org/content/65/8/1947It has been proposed that enzymes can associate into complexes (metabolons) that increase the efficiency of metabolic pathways by channelling substrates between enzymes. Metabolons may increase flux by increasing the local concentration of intermediates, decreasing the concentration of enzymes needed to maintain a given flux, directing the products of a pathway to a specific subcellular location or minimizing the escape of reactive intermediates. Metabolons can be formed by relatively loose non-covalent protein-protein interaction, anchorage to membranes, and (in bacteria) by encapsulation of enzymes in protein-coated microcompartments. Evidence that non-coated metabolons are effective at channelling substrates is scarce and difficult to obtain. In plants there is strong evidence that small proportions of glycolytic enzymes are associated with the outside of mitochondria and are effective in substrate channelling. More recently, synthetic metabolons, in which enzymes are scaffolded to synthetic proteins or nucleic acids, have been expressed in microorganisms and these provide evidence that scaffolded enzymes are more effective than free enzymes for metabolic engineering. This provides experimental evidence that metabolons may have a general advantage and opens the way to improving the outcome of metabolic engineering in plants by including synthetic metabolons in the toolbox

Building the Evryscope: Hardware Design and Performance

The Evryscope is a telescope array designed to open a new parameter space in optical astronomy, detecting short timescale events across extremely large sky areas simultaneously. The system consists of a 780 MPix 22-camera array with an 8150 sq. deg. field of view, 13" per pixel sampling, and the ability to detect objects down to Mg=16 in each 2 minute dark-sky exposure. The Evryscope, covering 18,400 sq.deg. with hours of high-cadence exposure time each night, is designed to find the rare events that require all-sky monitoring, including transiting exoplanets around exotic stars like white dwarfs and hot subdwarfs, stellar activity of all types within our galaxy, nearby supernovae, and other transient events such as gamma ray bursts and gravitational-wave electromagnetic counterparts. The system averages 5000 images per night with ~300,000 sources per image, and to date has taken over 3.0M images, totaling 250TB of raw data. The resulting light curve database has light curves for 9.3M targets, averaging 32,600 epochs per target through 2018. This paper summarizes the hardware and performance of the Evryscope, including the lessons learned during telescope design, electronics design, a procedure for the precision polar alignment of mounts for Evryscope-like systems, robotic control and operations, and safety and performance-optimization systems. We measure the on-sky performance of the Evryscope, discuss its data-analysis pipelines, and present some example variable star and eclipsing binary discoveries from the telescope. We also discuss new discoveries of very rare objects including 2 hot subdwarf eclipsing binaries with late M-dwarf secondaries (HW Vir systems), 2 white dwarf / hot subdwarf short-period binaries, and 4 hot subdwarf reflection binaries. We conclude with the status of our transit surveys, M-dwarf flare survey, and transient detection.Comment: 24 pages, 24 figures, accepted PAS