Non-market use and non-use values for preserving ecosystem services over time : a choice experiment application to coral reef ecosystems in New Caledonia

Non-use values (i.e. economic values assigned by individuals to ecosystem goods and services unrelated to current or future uses) provide one of the most compelling incentives for the preservation of ecosystems and biodiversity. Assessing the non-use values of non-users is relatively straightforward using stated preference methods, but the standard approaches for estimating non-use values of users (stated decomposition) have substantial shortcomings which undermine the robustness of their results. In this paper, we propose a pragmatic interpretation of non-use values to derive estimates that capture their main dimensions, based on the identification of a willingness to pay for ecosystem protection beyond one's expected life. We empirically test our approach using a choice experiment conducted on coral reef ecosystem protection in two coastal areas in New Caledonia with different institutional, cultural, environmental and socio-economic contexts. We compute individual willingness to pay estimates, and derive individual non-use value estimates using our interpretation. We find that, a minima, estimates of non-use values may comprise between 25 and 40% of the mean willingness to pay for ecosystem preservation, less than has been found in most studies.

A quay crane scheduling methodology for multimodal container terminals

This thesis develops an operational decision support tool for container terminal managements. The tool generates efficient schedules for shore cranes handling containers carried by mega container vessels.

Aerothermal-strucutral analysis of a rocket launched Mach 8 scramjet experiment : ascent

This paper reports on the methodology and results of a weak-coupled aerothermalstructural analysis on the ascent phase of the SCRAMSPACE Mach 8 scramjet flight experiment. This vehicle was essentially un-shrouded during the flight trajectory, relying on the thin, 5mm thick aluminium external shell of the payload to maintain structural integrity and protect the flight experiment. As such, understanding the thermal-structural response of the vehicle was imperative to mission success. Using two- and three-dimensional models, an iterative procedure was employed to compute the flowfield, convective heating, wall temperatures and structural coupling at flight times covering both peak heating and peak surface temperature. Accounting for such coupling resulted in a 150K reduction in wall temperature compared to the more conservative cold wall assumption. Despite this, peak temperatures remained of the order of 550 K. Further, thermally induced stresses within these regions were in excess of four times the material failure limits. Irreversible material failure during ascent was therefore concluded likely to occur on the external shell. Two alternate materials, steel 1006 and copper, were therefore assessed with the results indicating that steel sections on the external shell resulted in the best thermal-structural response of the payload.

An improved modal strain energy method for structural damage detection, 2D simulation

Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.

An experiment in collaborative writing

We’re starting 2015 with an experiment in collaborative creative writing. What happens when you ask ten academics to write a story together? Taking our cue from the Exquisite Cadaver game played by Surrealist artists and poets in the 1930s, we’ve asked our authors to contribute to a story in progress. We gave them free rein: no restrictions on style or genre.

Exit polls, turnout, and bandwagon voting: Evidence from a natural experiment

We exploit a voting reform in France to estimate the causal effect of exit poll information on turnout and bandwagon voting. Before the change in legislation, individuals in some French overseas territories voted after the election result had already been made public via exit poll information from mainland France. We estimate that knowing the exit poll information decreases voter turnout by about 11 percentage points. Our study is the first clean empirical design outside of the laboratory to demonstrate the effect of such knowledge on voter turnout. Furthermore, we find that exit poll information significantly increases bandwagon voting; that is, voters who choose to turn out are more likely to vote for the expected winner.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

‘Blind Faith’. An experiment with narrative agency in game design

This paper reports on the current field of narrative-based game design through case study analysis with a particular focus on balancing high narrative agency with low production resources.

BPMVM Evaluation Experiment Materials

All the materials used for our two experimental studies for evaluating the BPMVM modeller.

Refractory boron compounds for high performance: Theory and experiment

We have shown that novel synthesis methods combined with careful evaluation of DFT phonon calculations provides new insight into boron compounds including a capacity to predict Tc for AlB2-type superconductors.

Introducing the multi-faceted teaching experiment

A mathematics classroom is comprised of many mathematicians with varying understanding of mathematics knowledge, including the teacher, students and sometimes researchers. To align with this conceptualisation of knowledge and understanding, the multi-faceted teaching experiment will be introduced as an approach to study all classroom participants’ interactions with the shared knowledge of mathematics. Drawing on the experiences of a large curriculum project, it is claimed that, unlike a multi-tiered teaching experiment, the multi-faceted teaching experiment provides a research framework that allows for the study of mathematicians’ building of knowledge in a classroom without privileging the experience of any one participant.

Novel application of a discrete choice experiment to identify preferences for a national healthcare-associated infection surveillance programme: A cross-sectional study

Objective: To identify key stakeholder preferences and priorities when considering a national healthcare-associated infection (HAI) surveillance programme through the use of a discrete choice experiment (DCE). Setting: Australia does not have a national HAI surveillance programme. An online web-based DCE was developed and made available to participants in Australia. Participants: A sample of 184 purposively selected healthcare workers based on their senior leadership role in infection prevention in Australia. Primary and secondary outcomes: A DCE requiring respondents to select 1 HAI surveillance programme over another based on 5 different characteristics (or attributes) in repeated hypothetical scenarios. Data were analysed using a mixed logit model to evaluate preferences and identify the relative importance of each attribute. Results: A total of 122 participants completed the survey (response rate 66%) over a 5-week period. Excluding 22 who mismatched a duplicate choice scenario, analysis was conducted on 100 responses. The key findings included: 72% of stakeholders exhibited a preference for a surveillance programme with continuous mandatory core components (mean coefficient 0.640 (p<0.01)), 65% for a standard surveillance protocol where patient-level data are collected on infected and non-infected patients (mean coefficient 0.641 (p<0.01)), and 92% for hospital-level data that are publicly reported on a website and not associated with financial penalties (mean coefficient 1.663 (p<0.01)). Conclusions: The use of the DCE has provided a unique insight to key stakeholder priorities when considering a national HAI surveillance programme. The application of a DCE offers a meaningful method to explore and quantify preferences in this setting.