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Early Cretaceous continental-scale sediment dispersal: Towards resolving the McMurray conundrum - Discussion
(Society for Sedimentary Geology (SEPM), 2026) Dashtgard, Shahin E.; Gingras, Murray K.; Ranger, Mike; La Croix, Andrew D.; MacEachern, James A.
Wahbi et al. (2025) addresses aspects of the oilsands-hosting McMurray Formation (Fm) in northeast Alberta, Canada. As one of the largest petroleum reservoirs on Earth, resolving the geology of the McMurray Fm has potentially wide-ranging economic implications, and so the interval has received significant research attention. As noted by Wahbi et al. (2025), differing interpretations of the McMurray Fm stem largely from varying assessments of the degree of marine influence, and this is commonly referred to as the “McMurray conundrum” (Gingras and Leckie 2017; Gingras et al. 2019). At its core, the McMurray conundrum describes the seemingly irreconcilable juxtaposition of: 1) fluvial architectures (point bars and channel belts) that are associated mainly with the C2 through A2 parasequences and some evidence that the regional parasequences were deposited in freshwater (terrestrial) environments; versus 2) the preservation of bioturbation in both sand beds and the mudstone layers that drape point bar surfaces (i.e., inclined heterolithic stratification) coupled with the minimal preservation of terrestrial strata (e.g., floodplain deposits, coal beds, and paleosols).
Seismic porosity estimation using geologically-informed seismic attributes and a kriging-enhanced random forest: Application to a shallow-marine carbonate reservoir
(Springer, 2026-05-08) Rezaei, Mohammadali; La Croix, Andrew D.; Emami Niri, Mohammad; Asghari, Omid
Reliable property modeling is vital for Earth resource development, and seismic data can provide secondary variables to improve accuracy. However, seismic-integrated models remain uncertain due to inherent limitations in seismic data such as the cumulative effects of signal processing and attribute computation. In this study, we aimed to estimate a high-accuracy 3D secondary variable for porosity modeling from seismic attributes using a kriging-enhanced random forest (RF). This approach leverages the ensemble learning capabilities of RF to effectively handle limited training data, while incorporating the ability of kriging to account for spatial correlation. Prior to implementing this model, we developed an innovative workflow to correct seismic attributes based on geological trends. This workflow generated geologically informed seismic attributes by vertically correcting seismic attributes in areas of lower quality, while preserving their original lateral trends. We applied our methodology to a late Albian–early Turonian shallow-marine carbonate reservoir with a complex diagenetic history. After creating geologically informed seismic attributes, we used them, along with porosity well logs, as inputs for the kriging-enhanced RF model. This model calculated the mean of decision trees through kriging estimation rather than the usual averaging method. To evaluate effectiveness, we compared it with a deep neural network, a kriging-enhanced deep neural network, and a standard RF. The kriging-enhanced RF produced porosity closer to blind-well values than other methods and captured complex heterogeneities, such as channels and differing reservoir qualities across sequences, making the porosity cube a reliable 3D trend for further geostatistical simulations.
Exploring the relationship between age and victimisation risk
(The University of Waikato, 2026) Steer, Donelle; Tompson, Lisa
Extensive research has examined the relationship between age and offending, which is reflected in the established age-crime curve. The age-crime curve shows that offending typically rises during adolescence, peaks in late adolescence, and declines through the twenties and beyond. But less attention has been given to investigating age-related patterns of victimisation. Therefore, in this thesis we1 sought to answer two research questions. First, is there an age-victimisation curve comparable to the well-established age-crime curve? Second, if present, does the age-victimisation curve differ across broad crime categories (property vs interpersonal crime)? To answer these questions, we analysed data from two main sources – the New Zealand Recorded Crime Victims Statistics (RCVS) and the New Zealand Crime and Victims Survey (NZCVS). We plotted both the frequency and rates of victimisation across age using line graphs. For both our research questions, we found that there were age-victimisation curves that mirrored the age-crime curve for the RCVS samples, but not necessarily for our NZCVS samples. Generally, our research showed that the rate and frequency of victimisation increases from teenage years well into people’s twenties, before decreasing as age increases. However, the NZCVS samples showed a gradual decline rather than a discernible curve, with some spikes around middle adulthood. Future research should use longitudinal data to better understand the distribution of victimisation over the life-course and examine the age of onset of victimisation to inform targeted prevention and intervention efforts.
How can we make a diverse range of aromatic sulfates to explore sulfatase substrate relationships?
(The University of Waikato, 2026-05-16) Wang, Peiyao; Dickson, Benjamin
Antibody–drug conjugates (ADCs) are an emerging class of targeted therapeutics that combine the high specificity of monoclonal antibodies (mAbs) with the potent cytotoxicity of small-molecule drugs. A critical component of ADC design is the linker between mAbs and payload, as its chemical stability and cleavage behaviour directly determine therapeutic efficacy, selectivity, and safety. While peptide-based cleavable linkers dominate current clinical ADC platforms, their susceptibility to premature cleavage and instability in certain biological contexts has motivated the exploration of alternative enzymatically cleavable linkers. Arylsulfatase-cleavable linkers have recently attracted increasing interest as a promising alternative due to their excellent efficiency and reported stability in both human and mouse plasma. The cleavage of sulfate is catalysed by lysosomal sulfatases. Sulfatases were expressed in some tumour environments, which further support the selectivity of ADCs. However, systematic study for the characterization of structure and the analysis of properties is still insufficient, which limited the development of sulfatase-cleavable linker in certain degree. In this study, a diverse library of substituted aryl sulfates was synthesised to probe sulfatase–substrate interactions and to establish a robust analytical framework for their characterisation. The synthetic strategy enabled the preparation of aryl sulfates bearing a range of electron-donating and electron-withdrawing substituents at different positions on the aromatic ring, allowing systematic evaluation of electronic and structural effects. The resulting compounds were fully characterised using nuclear magnetic resonance (NMR), high-performance liquid chromatography (HPLC), mass spectrometry (MS), and UV–visible (UV–Vis) spectroscopy.
Process integration and electrification with digital twins
(The University of Waikato, 2026-05-14) Lincoln, Benjamin James; Walmsley, Timothy Gordon; Atkins, Martin John; Walmsley, Michael R.W.; Young, Brent R.
The decarbonisation of industrial process heat is one of the most pressing challenges in the global energy transition. In New Zealand, fossil fuels remain the dominant source of process heat, despite having over 80% renewable electricity generation. Milk powder production is a major consumer of process heat, with evaporation and drying processes relying on large amounts of coal- and gas-fired steam. Electrification technologies such as industrial heat pumps and mechanical vapour recompression (MVR) have the potential to significantly reduce emissions, yet widespread adoption has been limited because of the complex interactions between heat and power, in addition to uncertainties around practicality. Conventional process integration (PI) techniques were designed for fossil-fuelled utilities and are poorly aligned with the work requirements and integration constraints of electrification. Meanwhile, legacy simulation tools are ill-suited to the complex fluids and system interactions of food and dairy processes. This thesis addresses these gaps by developing a generalisable Process Integration and Electrification (PI&E) methodology that combines exergy-based targeting, retrofit strategies, and techno-economic evaluation coupled with an iterative design-centric digital twin framework. The thesis is structured in two parts. Part A develops the digitalisation foundations, including the preparation of a milk evaporation case study, the creation of advanced thermophysical property packages for complex fluids (milk, refrigerants, humid air), and the construction of a design digital twin using both commercial and open-source platforms. Part B applies the digital twin to PI&E, integrating operational optimisation, Exergy Pinch Analysis, and systematic evaluation of electrification technologies in both greenfield and retrofit contexts. For greenfield design, the research extends Pinch Analysis principles to heat pump integration by utilising heat pockets to create multiple Pinch points, enabling systematic minimisation of temperature lift and improved integration opportunities. Building on this, an iterative PI&E design workflow was developed to guide technology placement and evaluate electrification pathways. This culminated in the design of a novel fully electric milk evaporator system that achieved a specific electricity consumption of 120 kWh per tonne of milk powder, compared with 159 kWh/tp for a simpler single heat pump design, demonstrating higher efficiency. For retrofit applications, the thesis advances PI&E by extending heat pump bridge analysis to explicitly include process unit heat flows, allowing process modifications to be considered alongside heat exchanger reconfiguration. This innovation addresses a key gap identified in previous literature, enabling more retrofit strategies. The method was demonstrated through multiple related case studies of milk evaporator plants, producing a set of common retrofit solutions. These include replacing thermal vapour recompression (TVR) and/or direct steam injection with MVR systems, which were shown to deliver lower levelised costs of heat compared with reference boiler-based designs. The culmination of the research is a unified PI&E methodology that combines digital twins, rigorous thermodynamic analysis, and practical integration strategies. The results show that electrification of milk evaporation systems can be achieved in both new and existing plants with significant efficiency gains and competitive economics. PI&E has been tested across multiple platforms: Aspen HYSYS, DWSIM and the Ahuora Digital Twin Platform, powered by IDAES – proving to be a platform-agnostic, yet digitalisation-centred, methodology. Although developed and applied in the context of New Zealand’s dairy sector, the methods and insights are broadly transferable to other low- to medium-temperature process industries, offering a robust and scalable pathway to accelerate industrial decarbonisation.