The 'New Queenslander': A Contemporary Environmentally Sustainable Timber House

This paper describes the outcomes of an applied research project aimed at developing a contemporary, environmentally sustainable housing approach that takes its lead from the qualities and attributes of the Queensland vernacular timber housing, and that can be widely adopted in a similar way to its traditional predecessor. There was no intention to revive the original ‘Queenslander’ house but to build on the qualities which have made the timber house such an attractive and sustainable housing typology to develop a contemporary timber design vocabulary for project homes in Queensland. The design-led multi-disciplinary project took a critical approach to identifying the optimum solution that can be obtained by combining available building materials with market appeal and affordability, architectural design for lifestyle in Australian subtropical and tropical climates, engineering design, and environmental performance. It was also imperative that the timber systems developed be able to be adopted by the house building industry with minimal change to the conventional trade-based process of project delivery. The research included a review of available timber products including composite products, and a review of regulatory issues which impact on the use of timber in residential construction. The findings of the reviews were combined with environmental design objectives to develop a new construction system for integrating timber products in residential design

Human-chimpanzee coexistence at Bossou, the Republic of Guinea: a chimpanzee perspective

The increasing rate of human population growth has expanded the human-primate interface, with more conversion of natural primate habitat to agricultural land. Elevated levels of crop-raiding by primates are a by-product of natural resources becoming less available, and the nutritional riches of agricultural production becoming increasingly known to the primates. It was the aim of this thesis to focus on the Bossou chimpanzees’ (Pan troglodytes verus) perspective of their habitat in the Republic of Guinea, West Africa, the risks and opportunities presented by a human-dominated landscape, and to detail their day-to-day coexistence with humans. I combined a variety of data collection techniques, from focal, scan and ad libitum behavioural sampling of the chimpanzees’ daily activities, to broad ecological and habitat surveys. The chimpanzees rely on cultivated foods, and thus are forced to respond to humans. However, significant variation in the importance of various cultivars in the chimpanzees’ diet exists; certain cultivars are mostly fallback foods, while others are preferred food items and taken according to their availability in orchards and fields. The usage patterns of wild and cultivated foods by the chimpanzees of Bossou are thus inextricably connected. Whilst engaged in crop-raiding the chimpanzees exhibit several behavioural adaptations, namely a decrease in vocalisation levels, and increases in the transportation of food and specific vigilance behaviour. Adult males and adult male-only parties crop-raid more than other age- and sex-classes/compositions, and are more likely to take risks by raiding in exposed environments with increased risk of human confrontation. The use of human cultivars also affects the socio-sexual behaviour of the chimpanzees: chimpanzees appear to share the fruits of their risky labours (crop-raiding) as a food-for-sex strategy, which allow adult males to advertise prowess and enhance affiliative relationships with reproductively valuable females (Hockings et al., in prep). In addition, behavioural adaptations to other anthropogenic high-risk situations such as road-crossing were found, with the chimpanzees exhibiting impressive levels of socio-spatial flexibility and cooperation (Hockings et al., 2006). The chimpanzees’ level of anxiety (as measured by rough self-directed scratching) increases when dealing with some of the challenges posed by their physical and social environment. The chimpanzees of Bossou have been forced to adapt ecologically and behaviourally to the various costs and benefits of living in a human-dominated environment.This study was made possible by a studentship provided by the Department of Psychology at the University of Stirling, and fieldwork expenses provided by Professor Matsuzawa (from JSPS-HOPE and MEXT (#16002001))

Secondary driver mutations in CEBPA-mutated Acute Myeloid Leukaemia

In this thesis I explored the role of the transcription factor CEBPA in leukaemogeneis by creating novel cebpa mutant zebrafish lines modelling mutations found in sporadic AML. These recapitulated the two well-described categories of CEBPA mutation: CEBPA Nterm, mutations in the N terminus of full length CEBPA inducing a frameshift mutation prior to the internal reading frame, and Cterm, encoding an in-frame defect in the bZIP DNA binding domain coded in the C terminus. Primitive and definitive haematopoiesis were studied during embryonic development in both biallelic and heterozygous mutants. This revealed marked defects in production of mature granulocytes and monocytes in all biallelic mutants. Myeloid progenitor cell numbers in all biallelic mutants and N term heterozygotes were also markedly reduced. Distinct phenotypes were also seen between the two mutations highlighting their functional differences. Biallelic mutants with cebpaNterm showed an increase in HSPCs expressing myb, presumed to have undergone myeloid priming. However, early HSPC numbers expressing cd41 and runx1 showed no alteration in number. Haematopoiesis was also studied in juvenile and adult zebrafish. Survival was poor in biallelic mutants, with leukaemia developing in the presence of cebpaNterm before eight weeks of age. This was not seen in cebpaCterm/Cterm, where expansion in HSPCs and myeloid progenitors was observed without subsequent leukaemic transformation

A Biologically Motivated Software Retina for Robotic Sensors Based on Smartphone Technology

A key issue in designing robotics systems is the cost of an integrated camera sensor that meets the bandwidth/processing requirement for many advanced robotics applications, especially lightweight robotics applications, such as visual surveillance or SLAM in autonomous aerial vehicles. There is currently much work going on to adapt smartphones to provide complete robot vision systems, as the phone is so exquisitely integrated having camera(s), inertial sensing, sound I/O and excellent wireless connectivity. Mass market production makes this a very low-cost platform and manufacturers from quadrotor drone suppliers to children’s toys, such as the Meccanoid robot, employ a smartphone to provide a vision system/control system. Accordingly, many research groups are attempting to optimise image analysis, computer vision and machine learning libraries for the smartphone platform. However current approaches to robot vision remain highly demanding for mobile processors such as the ARM, and while a number of algorithms have been developed, these are very stripped down, i.e. highly compromised in function or performance For example, the semi-dense visual odometry implementation of [1] operates on images of only 320x240pixels. In our research we have been developing biologically motivated foveated vision algorithms, potentially some 100 times more efficient than their conventional counterparts, based on a model of the mammalian retina we have developed. Vision systems based on the foveated architectures found in mammals have the potential to reduce bandwidth and processing requirements by about x100 - it has been estimated that our brains would weigh ~60Kg if we were to process all our visual input at uniform high resolution. We have reported a foveated visual architecture that implements a functional model of the retina-visual cortex to produce feature vectors that can be matched/classified using conventional methods, or indeed could be adapted to employ Deep Convolutional Neural Nets for the classification/interpretation stage, [2,3,4]. We are now at the early stages of investigating how best to port our foveated architecture onto a smartphone platform. To achieve the required levels of performance we propose to optimise our retina model to the ARM processors utilised in smartphones, in conjunction with their integrated GPUs, to provide a foveated smart vision system on a smartphone. Our current goal is to have a foveated system running in real-time to serve as a front-end robot sensor for tasks such as general purpose object recognition and reliable dense SLAM using a commercial off-the-shelf smartphone which communicates with conventional hardware performing back-end visual classification/interpretation. We believe that, as in Nature, space-variance is the key to achieving the necessary data reduction to be able to implement the complete visual processing chain on the smartphone itself

Assessment of management effectiveness for the 2009 Great Barrier Reef Outlook Report

Independent assessment of management effectiveness conducted to inform the Great Barrier Reef Outlook Report 2009

A Biologically Motivated Software Retina for Robotic Sensors for ARM-Based Mobile Platform Technology

A key issue in designing robotics systems is the cost of an integrated camera sensor that meets the bandwidth/processing requirement for many advanced robotics applications, especially lightweight robotics applications, such as visual surveillance or SLAM in autonomous aerial vehicles. There is currently much work going on to adapt smartphones to provide complete robot vision systems, as the smartphone is so exquisitely integrated by having camera(s), inertial sensing, sound I/O and excellent wireless connectivity. Mass market production makes this a very low-cost platform and manufacturers from quadrotor drone suppliers to children’s toys, such as the Meccanoid robot [5], employ a smartphone to provide a vision system/control system [7,8]. Accordingly, many research groups are attempting to optimise image analysis, computer vision and machine learning libraries for the smartphone platform. However current approaches to robot vision remain highly demanding for mobile processors such as the ARM, and while a number of algorithms have been developed, these are very stripped down, i.e. highly compromised in function or performance. For example, the semi-dense visual odometry implementation of [1] operates on images of only 320x240pixels. In our research we have been developing biologically motivated foveated vision algorithms based on a model of the mammalian retina [2], potentially 100 times more efficient than their conventional counterparts. Accordingly, vision systems based on the foveated architectures found in mammals have also the potential to reduce bandwidth and processing requirements by about x100 - it has been estimated that our brains would weigh ~60Kg if we were to process all our visual input at uniform high resolution. We have reported a foveated visual architecture [2,3,4] that implements a functional model of the retina-visual cortex to produce feature vectors that can be matched/classified using conventional methods, or indeed could be adapted to employ Deep Convolutional Neural Nets for the classification/interpretation stage. Given the above processing/bandwidth limitations, a viable way forward would be to perform off-line learning and implement the forward recognition path on the mobile platform, returning simple object labels, or sparse hierarchical feature symbols, and gaze control commands to the host robot vision system and controller. We are now at the early stages of investigating how best to port our foveated architecture onto an ARM-based smartphone platform. To achieve the required levels of performance we propose to port and optimise our retina model to the mobile ARM processor architecture in conjunction with their integrated GPUs. We will then be in the position to provide a foveated smart vision system on a smartphone with the advantage of processing speed gains and bandwidth optimisations. Our approach will be to develop efficient parallelising compilers and perhaps propose new processor architectural features to support this approach to computer vision, e.g. efficient processing of hexagonally sampled foveated images. Our current goal is to have a foveated system running in real-time on at least a 1080p input video stream to serve as a front-end robot sensor for tasks such as general purpose object recognition and reliable dense SLAM using a commercial off-the-shelf smartphone. Initially this system would communicate a symbol stream to conventional hardware performing back-end visual classification/interpretation, although simple object detection and recognition tasks should be possible on-board the device. We propose that, as in Nature, foveated vision is the key to achieving the necessary data reduction to be able to implement complete visual recognition and learning processes on the smartphone itself

A Software Retina for Egocentric & Robotic Vision Applications on Mobile Platforms

We present work in progress to develop a low-cost highly integrated camera sensor for egocentric and robotic vision. Our underlying approach is to address current limitations to image analysis by Deep Convolutional Neural Networks, such as the requirement to learn simple scale and rotation transformations, which contribute to the large computational demands for training and opaqueness of the learned structure, by applying structural constraints based on known properties of the human visual system. We propose to apply a version of the retino-cortical transform to reduce the dimensionality of the input image space by a factor of ex100, and map this spatially to transform rotations and scale changes into spatial shifts. By reducing the input image size accordingly, and therefore learning requirements, we aim to develop compact and lightweight egocentric and robot vision sensor using a smartphone as the target platfor

Recovery and Management in Surin Marine National Park, Thailand

Reefs around Surin were affected by the 26 December tsunami differently depending on the marine topography, the dominant coral types and the direction of striking waves. Major waves struck Surin three times. The first was from the north-west to southeast, the second was the reverse, from southeast to northwest and the third was again from the northwest to southeast. A survey of the impact of the tsunami on Surin's reefs was undertaken using the same method applied to monitoring the site since 1998 (Department of Marine Science, Kasetsart University). While individual coral forms were effected (Table 1), long lasting effects were generally minor. The scale of impact on individual coral colonies was high but the colonies were not destroyed. Large massive corals were up-turned but were not killed, branching coral colonies were move but survived the shift and many colonies were covered by sand but rapidly uncovered by current with minimal detriment. While some sites were severely affected by the tsunami, overall the reef of Surin can be considered to be a minor affected area. Of greater concern is the slow re-establishment of a management presence to control tourism use and illegal fishing. Unfettered, both have the potential to result in a greater decline in reef condition than that identified from the tsunami