Griffith Research Online

This chapter delves into the nature and significance of evidence within the context of hypothesis testing, advocating for the use of multiple data types for triangulation. The selection of specific data sources and indicators is emphasised, tailored to the nuanced requirements of investigating realist hypotheses. Initially, parallels are drawn between evidentiary practices in courts and scientific endeavours, setting the stage for a discussion of the realist framework. Subsequently, through examples drawn from crime-related evaluations, the drawbacks and advantages of various data sources - such as recorded crime data, victimisation surveys, observational data and interviews - are explored. Notably, the potential benefits of employing unobtrusive measures, including refuse data, are highlighted. Using a project evaluating police patrols as a case study, the integration of refuse data alongside other sources is illustrated, demonstrating its utility in addressing hypotheses. While acknowledging limitations, such as those inherent in physical evidence like refuse data, it is underscored as a valuable supplementary source for confirming, refuting or refining realist hypotheses.

Humpback whales Megaptera novaeangliae encounter a variety of environmental conditions during seasonal migration between feeding grounds and breeding grounds. Relationships between environmental conditions and migratory movements are largely unknown due to a lack of oceanographic data coincident with their presence/absence. We begin to address this knowledge gap by developing a new agent-based modelling (ABM) approach designed to predict southward migration of mother–calf (MC) pairs along a stretch of the east Australian coast between the Great Barrier Reef (GBR) and Gold Coast (GC) bay, which includes a known resting area, Hervey Bay (HB). To assess our ability to reproduce observed migration patterns, numerical experiments were undertaken in which static (bathymetry) and dynamic (currents, sea surface temperature) variables between August and October 2017 governed movements. These experiments revealed how bathymetry influences HB usage, and a necessity to apply different directionality preferences to whales before and after negotiating HB, which appear to closely align with coastline orientation. The ABM provides a novel, suitable framework for simulating MC humpback whale migration, and an important first step in the development of predictive models of humpback whale behavior. Developing such tools is increasingly necessary to predict how changing ocean conditions are likely to affect their distribution.

Omaveloxolone was recently approved by the U.S. Food and Drug Administration (FDA) as the designated treatment for Friedreich ataxia (FRDA),1 an autosomal recessive disorder caused by mutations in the frataxin gene. FRDA is characterized by ataxia and cardiomyopathy.2-4 The pathogenesis of FRDA can be attributed to frataxin deficiency, which leads to increased oxidative stress, impaired nuclear factor erythroid 2-related factor 2 (Nrf2) signaling, dysregulated metal homeostasis, and chronic inflammation.5, 6 Omaveloxolone is an activator of Nrf2, which aims to counteract these pathologies by enhancing the expression of antioxidant enzymes and restoring redox balance, which is dysregulated in FRDA.7, 8 Although both preclinical and clinical studies have shown promising outcomes regarding neurological function, the impact of omaveloxolone on cardiovascular outcomes in FRDA remains unclear. The scarcity of literature addressing the cardiovascular effects of omaveloxolone in FRDA is concerning, especially considering that cardiomyopathy is the primary cause of mortality in affected individuals. Furthermore, the reported potential of omaveloxolone to induce mild elevations in B-natriuretic peptide (BNP),9, 10 a known marker of heart failure, adds to this concern. Thus, those individuals with FRDA who have cardiomyopathy are advised to monitor BNP levels while using omaveloxolone.9 In this viewpoint, we examine the current literature on the efficacy and safety of omaveloxolone in treating FRDA, with a focus on its potential impact on cardiovascular health.

In 2024 experts highlight misinformation and disinformation “amid elections” as the top short-term global risk. In addressing this pressing concern, electoral authorities are devising strategies to counter electoral disinformation while governments consider changes to public policy and legislation. Drawing on motivated reasoning theory, this study assesses the impact of disinformation and mitigation measures in Australia during the 2023 referendum campaign – to establish a constitutionally enshrined Indigenous Voice to Parliament – and its subsequent impacts on trust in the Australian Electoral Commission (AEC). Through a nationally representative survey experiment (N = 3825) we find overall high public trust in the AEC with disinformation having a small, but detectable effect. This study finds a level of “moral panic” regarding disinformation's threat to electoral integrity, at least in the Australian setting. However, concerningly, we also find existing AEC communication and refutation strategies have limited impact on countering distrust arising after a disinformation attack, suggesting a need for other strategies. Nonetheless, the study underscores the resilience of Australian electoral processes against disinformation threats serving as a caution against excessive legislative reaction to this global problem. Our study contributes to understanding the complex interplay between information, trust, and public policy responses to disinformation challenges.

Landslides are global hazards that contribute significantly to worldwide catastrophes. Since landslides cause fatalities and property damage, understanding movement patterns is crucial to mitigate risks or potential reactivations. Slope kinematic modeling can utilize geodetic surveying or direct observations, though Unmanned Aerial Vehicles with photogrammetric or laser scanning technologies have become prevalent in recent decades. This study introduces a new approach for monitoring landslides through UAV photogrammetry and LiDAR data. LiDAR and photogrammetry raster images were integrated by merging them according to landscape features, encompassing areas with vegetation and human-made structures. This fusion method leverages the complementary strengths of photogrammetry and LiDAR, optimizing their capabilities for distinct terrain features: photogrammetry excels in capturing detailed textures, while LiDAR penetrates vegetation to provide accurate ground-level data. By integrating these technologies, the Digital Feature Model (DFM) offers superior accuracy compared to conventional elevation models, making it particularly effective for monitoring complex terrains. To assess the robustness of the proposed methodology, 496 points were measured with topo-geodetic instruments within an active landslide, each point representing different terrain features. This analysis demonstrated the effective merging of data from both sensors, leading to thorough results that accurately represented the ground surface with the most suitable technology. The RMSE values for the vertical differences between the ground truth and the proposed DFM were 0.060 m, notably lower than the 0.206 m from photogrammetry and 0.441 m from LiDAR. This novel method can enhance the evaluation of landslide dynamics and movements, as follow-up surveys using this approach yield greater accuracy regarding differences between epochs.