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Exploring Seismicity around the Southern Central Section of the Alpine Fault, New Zealand, using Distributed Acoustic Sensing
No full textThe South Island Seismology at the Speed of Light Experiment (SISSLE) was an investigation of seismicity around the Alpine Fault, near Haast, New Zealand (NZ) using Distributed Acoustic Sensing (DAS) in 2023. In this study, measurements of seismicity were acquired on a 30 km long optical fibre that crossed the Alpine Fault and co-located nodes over an approximately three-month period. An analysis of this dataset is reported here.Coincident detection with manual arrival picking were used to identify the timing of 110 local (= 50 km) earthquakes detected at the nodes. This timing was used to identify earthquakes in the DAS archive which were manually picked. A subset of 25 of the local DAS records were then re-picked using a semi-automated manually guided picker developed to improve pick consistency. Delayed arrivals were noted at specific locations along the fibre in all records examined.These guided picks (excluding those that appeared to be delayed) were fitted using a least-squares approach based on ray tracing solutions to the Hamilton equations and NZ's current velocity model to determine earthquake hypocentres. Fitted epicentres were comparable to the epicentres reported by GeoNet where available. Fit uncertainties were assessed by introducing Gaussian noise proportional to the acoustic pathlength into the arrival data.Delayed arrivals, computed from the difference between the observed and fitted arrivals, varied systematically along the fibre suggesting that low-velocity structures were present. Motivated by correlations between valley reconstructions based on solutions to Laplace’s equation and the location of the delayed arrivals, it was proposed that these structures may be sediment-filled basins. Several basin topologies were investigated using a forward modelling approach. This modelling demonstrated that the measurements were insensitive to near-surface off-fibre structure and that the median arrival delay, , was approximately proportional to sediment depth z_sed, so that if the seismic velocity of the sediment is assumed to be constant v_sed then: z_sed=-v_sed×. This simple interpretation appears to be consistent with previously reported gravity and seismic reflection data on lines approximately co-located with the DAS fibre. Using a combination of ray tracing and wavefield modelling, `late’ fault zone head waves, that follow the direct arrivals, were predicted for a single local earthquake. These late fault zone head waves were not observed experimentally suggesting that the reflectivity of the Alpine Fault at Haast is low. `Early’ emergent arrivals were observed for two regional earthquakes located near the Alpine Fault. Because of the fibre’s orientation perpendicular to the fault, it was not possible to establish that these emergent arrivals were fault zone head waves from the DAS data alone. If these are in fact fault zone head waves, then the average velocity contrast Δv_P/v_P between the hanging wall and footwall of the Alpine Fault over approximately 100 km to the south and north of Haast are in the range 8.3–12 % and 1.8–2.5 %, respectively.</p
“INDIA, THE NEW MYTH”: Fictional Challenges to Official Historical Representations of the 1947 Independence and Partition of India
No full textThis thesis argues that fictional narratives centered around the 1947 Independence and Partition of India capture a greater nuance and holistic understanding of the events and their aftermath in comparison to their “official”, non-fictional counterparts. Primarily, this is because fictional narratives re-evaluate master narratives of Indian history and their validity to determine fixed notions of Indian identity and nationhood. However, more broadly, the form of fiction challenges the rigid historiographical approaches of “official” narratives to history, as fiction self-awarely incorporates the subjectivity of individual memory, experience and critical perspective in a way that emphasises history’s fluidity and ambiguity. These arguments are contextually underpinned by historical teleologies of the 1947 Independence and Partition of India that were adopted by both India and Pakistan as their official, master narratives of history. These purpose-driven narratives not only dilute and simplify historical events to fit a particular ideological prerogative, but validate the subcontinent’s present-day enforcement of minority marginalisation, religious separatism, cultural hegemony and national uniformity as predetermined by a historical “destiny." In an analysis of Saadat Hasan Manto’s “Khol Do” (1948), “Toba Tek Singh” (1955) and “The Dog of Tithwal” (1987), Salman Rushdie’s Midnight’s Children (1981), and Arundhati Roy’s The God of Small Things (1997), this thesis examines fictional representations around the dual historical events across diverse chronological points, critical theories, and literary genres. In doing so, the established “facts” of the events’ official teleological versions are exposed and reevaluated by new discourses. These fictional texts creatively highlight the inherent contextuality, ambiguity and absences of historical representation, thus embodying fiction’s more realistic search for historical truth rather than Indian historiography’s assignment of a concrete, objective purpose to the past. In undermining master narratives of history, and thus their claim to a totalising, statist form of nationhood, the collectivity of these fictional narratives reaffirm India’s identity as diverse, subjective, and multidimensional.</p
Religiosity and spirituality: An analysis of belief-based differences in moral and political attitudes
No full textIn New Zealand we have seen a decrease in those identifying as religious, and an increase in those identifying as spiritual. There are countless studies of how religious belief, and lack of, is associated with morality, values, and political belief but, as more and more people turn to non-denominational spirituality as an alternative way to practice faith, research is needed to understand how this growing population thinks and behaves. In Study One, several existing New Zealand datasets (Study 1A: from the Brainscan Survey, N = 4,023, Study 2A: from the New Zealand Attitudes and Values panel survey series [Time 3.5: N = 1,466], [Time 12: N = 37,745], [Time 13: N = 33,274]) were analysed to determine an overall picture of how these different belief systems are associated with, or potentially influence, moral, political and social attitudes. I found that, overall, results align with previous scholarship whereby ‘spiritual’ people tended to endorse Universalism, were more politically liberal, and endorsed Harm/Care moral foundations. Religious people tended to more strongly endorse Tradition, were more politically conservative, and endorsed Ingroup Loyalty and Fairness/Reciprocity moral foundations. Although these findings were robust, these separate constructs were spread over four datasets. Study Two aimed to remedy this, and involved a questionnaire completed by a sample of psychology undergraduates (N = 275), that assessed Moral Foundations, associated vignettes, political orientation, and attitudes towards groups. I found significant differences between the groups for all of the Moral Foundations (except Fairness/Reciprocity), political orientation, support for some of the New Zealand political parties (notably the National Party, Act Party, and the New Conservatives), and some attitudes towards groups (e.g. spiritual people had greater warmth towards those with a mental illness). Ultimately, these studies not only add to what we know about how belief manifests in people’s morality, attitudes, and eventual behaviour, but they have also included a large subset of the New Zealand’s population that is often overlooked under the umbrella of ‘atheist’, when in fact they hold faith-based beliefs.</p
Advanced Linear Genetic Programming and Applications to Dynamic Job Shop Scheduling
No full textLinear genetic programming (LGP) is an effective evolutionary computation method for searching symbolic solutions. It has been successfully applied to classification and symbolic regression problems and has shown superior performance in these problems because of its linear representation. However, existing studies have not applied LGP to design decision rules for dynamic combinatorial optimization problems. Designing decision rules for dynamic combinatorial optimization problems is substantially different from classification and symbolic regression problems (e.g., no target outputs and limited training instances), which poses new challenges to existing LGP studies. This thesis aims to propose advanced LGP methods and apply them to solve dynamic job shop scheduling (DJSS), a representative dynamic combinatorial optimization problem. More specifically, the overall goal of this thesis is to design LGP methods as a hyper-heuristic (GPHH) method for designing decision rules for DJSS. Our contributions focus on six aspects. First, this thesis develops an LGP-based hyper-heuristic (LGPHH) framework to effectively train LGP based on DJSS training instances. The LGPHH framework evolves based on a generational framework and initializes registers by diverse features. The results show that the proposed LGPHH method has a superior performance to a basic tree-based GPHH method and can design more compact decision rules than the tree-based one. Second, this thesis designs new graph-based search mechanisms for enhancing LGP performance. Specifically, we first investigate an effective way to transform the search information in graphs to LGP instructions. Based on the designed graph-to-instruction transformation, this thesis further proposes a multi-representation GP. The case study of tree-based and linear-based representation shows that the multi-representation GP framework significantly improves the performance of GP methods for DJSS. Third, this thesis proposes a grammar-guided LGP method to incorporate the domain knowledge of DJSS into LGP search. The grammar-guided LGP method includes a new grammar system, module context-free grammar, for defining grammar rules, and a set of grammar-guided genetic operators for evolving LGP based on the grammar rules. The results show that the proposed grammar-guided LGP can effectively design dispatching rules with IF operations to solve complicated DJSS problems. Fourth, this thesis proposes a fitness landscape optimization method to automatically optimize the neighborhood structures of LGP solutions to enhance LGP performance. The analyses on the optimized fitness landscape confirm that the proposed method significantly reduces the hardness of LGP fitness landscapes. The empirical results on common DJSS problems further verify that searching against the optimized fitness landscapes has a very competitive performance with advanced methods. Fifth, this thesis proposes an LGP-based multitask optimization framework based on the multi-output characteristic of LGP to make use of the interplay among similar DJSS problems. The results show that the proposed LGP-based multitask optimization framework has a superior performance to existing multitask GP methods for DJSS problems. Finally, this thesis further extends two of the advanced LGP methods (i.e., the multi-representation GP and the LGP with fitness landscape optimization) to symbolic regression problems. The superior performance for solving symbolic regression problems implies a good generality of the proposed methods in this thesis to other domains.</p
Open Science in the Developing World: A Collection of Practical Guides for Researchers in Developing Countries
No full textOver the past decade, the open-science movement has transformed the research landscape, although its impact has largely been confined to developed countries. Recently, researchers from developing countries have called for a redesign of open science to better align with their unique contexts. However, raising awareness alone is insufficient—practical actions are required to drive meaningful and inclusive change. In this work, we analyze the opportunities offered by the open-science movement and explore the macro- and micro-level barriers researchers in developing countries face when engaging with these practices. Drawing on these insights and aiming to inspire researchers in developing regions or other resource-constrained contexts to embrace open-science practices, we offer a four-level guide for gradual engagement: (a) foundation, using open resources to build a solid foundation for rigorous research; (b) growth, adopting low-cost, easily implementable practices; (c) community, contributing to open-science communities through actionable steps; and (d) leadership, taking on leadership roles or forming local communities to foster cultural change. We further discuss potential pitfalls of the current open-science practices and call for readaptation of these practices in developing countries’ settings. We conclude by outlining concrete recommendations for future action
Augmented Reality and the Metaverse - Speculating about the Future
No full textImagine a world where the boundaries between physical and digital realities dissolve, creating immersive experiences that transform how we interact. This potential lies at the heart of the Metaverse, and a confluence of technologies such as AR, VR, AI and blockchain will be the key to unlocking it. We employ a novel combination of horizon scanning and narrative development to explore the transformative role of AR within the Metaverse. This approach reveals potential technology-driven futures, highlighting emerging trends and disruptions not readily apparent through traditional forecasting methods. Our narratives of the future offer surprising glimpses into potential sociotechnical futures, informing a research agenda for both industry and academia
Three Essays on the Impacts of Weather Disasters: Evidence From New Zealand and Colombia
No full textThis thesis explores the multifaceted impacts of climate disasters on economic and psychological well-being across different contexts, using advanced econometric techniques and rich datasets. The first chapter examines the impact of rising temperatures on rural household expenditure in Colombia by combining high-resolution weather data with longitudinal household surveys. We find that a one-standard-deviation increase in average daily temperature during rainy months significantly reduces household expenditure, primarily through crop losses. While households respond by seeking non-agricultural jobs and liquidating livestock, these strategies fail to fully offset income losses due to limited access to risk-coping mechanisms. Wealth and rainfall mitigate some adverse effects. Our findings are robust to various specifications and alternative datasets.The second chapter investigates the economic impacts of two cyclone-induced floods on firms in New Zealand, using high-resolution satellite imagery and detailed business records. Employing a Difference-in-Differences (DID) approach, we find that flood-affected firms experienced significant declines in output, sales, profit, and value-added. Contrary to common assumptions, capital damage and labour displacement—rather than productivity losses—were the primary drivers of these effects. Firms responded by liquidating inventories and assets but showed no evidence of relocation. Results are robust across multiple econometric methods, including SDID.Finally, the third chapter uses a Synthetic Difference-in-Differences (SDID) approach to examine the mental health and earnings impacts of Cyclone Gabrielle on workers in New Zealand. Leveraging administrative data on prescribed medications and tax records, we find that workers in heavily damaged areas were more likely to be prescribed medication for psychological disorders than those in unaffected areas. Contrary to expectations, income losses played a limited role in mediating mental health impacts. Instead, physical and emotional trauma emerged as key drivers, underscoring the importance of non-economic factors in post-disaster recovery.</p
ADVANCING URBAN CARBON DIOXIDE (CO₂) INTERPRETATION FOR MODELING, MONITORING, AND EDUCATION
No full textCarbon dioxide (CO₂) is the most abundant greenhouse gas (GHG) and quantifying it in the atmosphere is critical for understanding and addressing climate change. With the expansion of in-situ monitoring networks, CO₂ observations have shifted their focus on global averages to finer spatial and temporal scales, enabling better emissions quantification and tracking changes in anthropogenic emissions. While these data are used in atmospheric inverse modeling to estimate emissions, their broader potential remains underexplored. Thus, this research addresses four research questions: (1) how can the use of in-situ GHG observations be expanded beyond afternoon hours in urban-scale atmospheric inverse modeling?, (2) what types of data analysis can be used to interpret atmospheric observations of urban CO₂ mole fractions? (3) what recommendations can be made for urban CO₂ background determination?, and (4) how can in-situ observations be used beyond scientific research within the context of carbon cycle education? To address these questions, this thesis is grounded in the analysis of atmospheric observations of urban CO₂ mole fractions, to advance the monitoring, modeling, and communication of urban CO₂ emissions.With in-situ atmospheric CO₂ observations from the INFLUX (Indianapolis Flux Experiment), I establish a criterion for incorporating non-afternoon observations, such as morning rush hour peaks, into atmospheric inverse modeling. Using CO₂ observations from the Auckland greenhouse gas network in Aotearoa New Zealand, I characterize the CO₂ mole fractions at urban and background sites and recommend analysis techniques applicable to other urban networks. By combining various atmospheric CO₂ observing technologies, I demonstrate when and how atmospheric observations can be used in education context and to track emissions changes.As such, this thesis adopts a multidisciplinary approach to improve urban CO₂ research and application, by integrating scientific, technical, and societal perspectives.</p
The Inadequacy and Neglect of Data Privacy Regulation in New Zealand: In Search of Meaningful Enforcement
No full textIn light of existing privacy regulations within New Zealand, this research examines the Privacy Act 2020 (“the Act”) and its impact within various contexts of criminal justice. Of interest is how s 31 of the Act (non-enforceability in court) affects the admissibility of evidence and, more importantly, policing practices. This work attempts to address intentional breaches of the Act, committed in pursuit of criminal prosecution. What happens when information privacy principles (IPPs) are breached? What is there to deter wrongdoing?This thesis argues that the Act’s approach to enforcement undermines its ability to deal with unique situations that arise in the context of criminal justice; in certain circumstances, repeated and large-scale breaches are effectively allowed. As a deterrent and safeguard, court-enforceable IPPs should be sought to combat reckless and opportunistic behaviour. It is proposed that existing mechanisms are limited by design and/or by circumstance.This research explores the judgment in R v Alsford, patterns of improper policing and emerging technologies.</p
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