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The white chalk cliffs on the south coast of England are one of the most iconic coastlines in the world. Rock coasts located in a weak lithology, such as chalk, are likely to be most vulnerable to climate-change-triggered accelerations in cliff retreat rates. In order to make future forecasts of cliff retreat rates as a response to climate change, we need to look beyond individual erosion events to quantify the long-term trends in cliff retreat rates. Exposure dating of shore platforms using cosmogenic radionuclide analysis and numerical modelling allows us to study past cliff retreat rates across the Late Holocene for these chalk coastlines. Here, we conduct a multi-objective optimisation of a coastal evolution model to both high-precision topographic data and 10Be concentrations at four chalk rock coast sites to reveal a link between cliff retreat rates and the rate of sea-level rise. Furthermore, our results strengthen evidence for a recent acceleration in cliff retreat rates at the chalk cliffs on the south coast of England. Our optimised model results suggest that the relatively rapid historical cliff retreat rates observed at these sites spanning the last 150 years last occurred between 5300 and 6800 years ago when the rate of relative sea-level rise was a factor of 5–9 times more rapid than during the recent observable record. However, results for these chalk sites also indicate that current process-based models of rock coast development are overlooking key processes that were not previously identified at sandstone rock coast sites. Interpretation of results suggest that beaches, cliff debris and heterogenous lithology play an important but poorly understood role in the long-term evolution of these chalk rock coast sites. Despite these limitations, our results reveal significant differences in intertidal weathering rates between sandstone and chalk rock coast sites, which helps to inform the long-standing debate of “wave versus weathering” as the primary control on shore platform development. At the sandstone sites, subaerial weathering has been negligible during the Holocene. In contrast, for the chalk sites, intertidal weathering plays an active role in the long-term development of the shore platform and cliff system. Overall, our results demonstrate how an abstract, process-based model, when optimised with a rigorous optimisation routine, can not only capture long-term trends in transient cliff retreat rates but also distinguish key erosion processes active in millennial-scale rock coast evolution at real-world sites with contrasting rock types.

Background: Approach bias modification (ApBM) and interpretation bias modification (IBM) are two promising adjunct treatments for alcohol use and social anxiety, respectively. However, the acceptability of combining ApBM and IBM into one program for people who experience both of these disorders is unknown. The present study describes the codevelopment of a new, hybrid ApBM + IBM program and provides insight into the perceptions of acceptability from service providers and emerging adults.Methods: Service providers (n = 14) and emerging adults aged 18 to 25 years with lived experience of hazardous alcohol use and heightened social anxiety (n = 15) were recruited via online advertisements and through existing networks. All participants were shown a beta version of the program and asked to complete qualitative and quantitative questions to ascertain feedback on the program's acceptability and suggestions for improvement.Results: Themes emerged relating to the ApBM + IBM program's quality and usefulness, appropriateness, motivation and engagement, and potential clinical value. The program was well received and deemed acceptable for the target age group. It was rated particularly highly with regard to the overall quality and ease of use. Emerging adults had fewer suggestions for how the intervention might be revised; however, there were suggestions from both groups regarding the need for a compelling rationale at the outset of treatment and a suggestion to include a motivational interviewing and psychoeducational-based module prior to the first training session, to increase user buy-in and engagement.Conclusions: The current findings reflect positively on the acceptability of a hybrid ApBM + IBM for emerging adults with co-occurring hazardous alcohol use and social anxiety. Service providers and emerging adults identified a number of ways to improve the design and implementation of the program, which will likely improve adherence to, and outcomes of, the intervention when added as an adjunct to treatment as usual.

Background Alcohol use and anxiety disorders commonly co-occur, resulting in a more severe clinical presentation and poorer response to treatment. Research has shown that approach bias modification (ApBM) and interpretation bias modification (IBM) cognitive retraining interventions can be efficacious adjunctive treatments that improve outcomes for alcohol use and social anxiety, respectively. However, the acceptability, feasibility, and clinical utility of combining ApBM and IBM programs to optimize treatments among comorbid samples are unknown. It is also unclear whether integrating ApBM and IBM within each training session or alternating them between each session is more acceptable and efficacious. Objective This paper describes the protocol for a randomized controlled pilot trial investigating the feasibility, acceptability, and preliminary efficacy of the Re-train Your Brain intervention—an adjunct web-based ApBM+IBM program—among a clinical sample of emerging adults with hazardous alcohol use and social anxiety. Methods The study involves a three-arm randomized controlled pilot trial in which treatment-seeking emerging adults (18-30 years) with co-occurring hazardous alcohol use and social anxiety will be individually randomized to receive the Re-train Your Brain integrated program, delivered with 10 biweekly sessions focusing on both social anxiety and alcohol each week, plus treatment as usual (TAU; ie, the model of care provided in accordance with standard practice at their service; n=30); the Re-train Your Brain alternating program, delivered with 10 biweekly sessions focusing on social anxiety one week and alcohol the next week, plus TAU (n=30); or TAU only (n=30). Primary outcomes include feasibility (uptake, follow-up rates, treatment adherence, attrition, and adverse events) and acceptability (system usability, client satisfaction, user experience, and training format preference). Secondary efficacy outcomes include changes in alcohol approach and interpretation biases, social anxiety, and alcohol use (eg, drinks per day, binge drinking, drinking motives, severity of dependence, and cravings). The primary end point will be posttreatment (6 weeks postbaseline), with a secondary end point at 3 months postbaseline. Descriptive statistics will be conducted for primary outcomes, whereas intention-to-treat, multilevel mixed effects analysis for repeated measures will be performed for secondary outcomes. Results This study is funded from 2019 to 2023 by Australian Rotary Health. Recruitment is expected to be completed by mid-2022 to late 2022, with follow-ups completed by early 2023. Conclusions This study will be the first to evaluate whether an ApBM+IBM program is acceptable to treatment-seeking, emerging adults and whether it can be feasibly delivered via the web, in settings where it will ultimately be used (eg, at home). The findings will broaden our understanding of the types of programs that emerging adults will engage with and whether the program may be an efficacious treatment option for this comorbidity. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12620001273976; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364131 International Registered Report Identifier (IRRID) PRR1-10.2196/28667

The risk from erosion and flooding in the coastal zone has the potential to increase in a changing climate. The development and use of coupled hydro-morphodynamic models is therefore becoming an ever higher priority. However, their use as decision support tools suffers from the high degree of uncertainty associated with them, due to incomplete knowledge as well as natural variability in the system. Here we show for the first time how the multilevel Monte Carlo method (MLMC) can be applied to hydro-morphodynamic models, in this case XBeach, to quantify uncertainty by computing statistics of output variables given uncertain input parameters. MLMC accelerates the Monte Carlo approach through the use of a hierarchy of models with different levels of resolution. A variety of theoretical and real-world coastal zone case studies are considered, for which output variables that are important to the assessment of flood and erosion risk are estimated, such as wave run-up height and total eroded volume. We show that MLMC can significantly reduce computational cost, resulting in speed up factors of 40 or greater compared to a simple Monte Carlo approach, whilst still maintaining the same level of accuracy. Furthermore, MLMC is used to estimate the cumulative distribution of these output variables for given uncertain parameters. This allows the risk of a variable exceeding a certain value to be calculated, for example the risk of the wave run-up height exceeding the height of a physical structure such as a seawall; this is a useful capability to inform decision-making processes.

This report describes the application and benchmarking of the Thetis coastal ocean model for tidal modelling, and makes use of a test case based upon the English Channel. Comparisons are made between model predictions and tide gauge data at a number of locations across the English Channel. A preliminary investigation of the impact of mesh resolution and bathymetry data is given. A demonstration is also provided of Thetis’s ability to use adjoint technology to optimise model predictions through the assimilation of observational data. In the example presented here the bottom friction field is optimised to provide an improved match between the model results and tide gauge data. This adjoint based optimisation capability may also be used to optimise the location, size and design of tidal power generation schemes.

Computational simulations of physical phenomena rely on an accurate discretisation of the model domain. Numerical models have increased in sophistication to a level where it is possible to support terrain-following boundaries that conform accurately to real physical interfaces, and resolve a multiscale of spatial resolutions. Whilst simulation codes are maturing in this area, pre-processing tools have not developed significantly enough to competently initialise these problems in a rigorous, efficient and recomputable manner. In the relatively disjoint field of Geographic Information Systems (GIS) however, techniques and tools for mapping and analysis of geographical data have matured significantly. If data provenance and recomputability are to be achieved, the manipulation and agglomeration of data in the pre-processing of numerical simulation initialisation data for geophysical models should be integrated into GIS. A new approach to the discretisation of geophysical domains is presented, and introduced with a verified implementation. This brings together the technologies of geospatial analysis, meshing and numerical simulation models. This platform enables us to combine and build up features, quickly drafting and updating mesh descriptions with the rigour that established GIS tools provide. This, combined with the systematic workflow, supports a strong provenance for model initialisation and encourages the convergence of standards.

High-resolution direct numerical simulations (DNSs) are an important tool for the detailed analysis of turbidity current dynamics. Models that resolve the vertical structure and turbulence of the flow are typically based upon the Navier–Stokes equations. Two-dimensional simulations are known to produce unrealistic cohesive vortices that are not representative of the real three-dimensional physics. The effect of this phenomena is particularly apparent in the later stages of flow propagation. The ideal solution to this problem is to run the simulation in three dimensions but this is computationally expensive. This paper presents a novel finite-element (FE) DNS turbidity current model that has been built within Fluidity, an open source, general purpose, computational fluid dynamics code. The model is validated through re-creation of a lock release density current at a Grashof number of 5 × 106 in two and three dimensions. Validation of the model considers the flow energy budget, sedimentation rate, head speed, wall normal velocity profiles and the final deposit. Conservation of energy in particular is found to be a good metric for measuring model performance in capturing the range of dynamics on a range of meshes. FE models scale well over many thousands of processors and do not impose restrictions on domain shape, but they are computationally expensive. The use of adaptive mesh optimisation is shown to reduce the required element count by approximately two orders of magnitude in comparison with fixed, uniform mesh simulations. This leads to a substantial reduction in computational cost. The computational savings and flexibility afforded by adaptivity along with the flexibility of FE methods make this model well suited to simulating turbidity currents in complex domains.

Explosive volcanic eruption events, in which large quantities of hot gas and ash are expelled high into the atmosphere, are one of the most powerful natural hazards. In order to gain a full understanding of the dangers these eruptions pose, their complex multiscale and multiphase nature must be captured to a high degree of accuracy. The application of numerical multiphase flow models often represents the only tenable way of achieving this, and permits the investigation of ash cloud evolution in domains many times larger than the laboratory-scale. However, even the most advanced models of eruption dynamics are restricted by the fixed mesh-based approaches that they generally employ. The research presented herein introduces a compressible multiphase flow model recently implemented within Fluidity, a combined finite element / control volume CFD code, for the study of explosive volcanic eruptions. Fluidity adopts an adaptive unstructured mesh-based approach to discretise the domain and focus numerical resolution only in areas important to the dynamics, while decreasing resolution where it is not needed as a simulation progresses. This allows the accurate but economical representation of the flow dynamics throughout time. The application of the model considers a 7 km × 7 km domain in which the violent eruption of hot gas and volcanic ash high into the atmosphere is simulated. It is shown by a convergence analysis that Fluidity offers the same solution accuracy for reduced computational cost using an adaptive unstructured mesh, compared to the same simulation performed with a fixed uniform mesh.

Innovation in R&D is a key target for the pharmaceutical sector to address some of the challenges it currently faces. This review discusses these challenges in the context of pharmaceutically relevant surfaces and interfaces. The surface properties of materials determine many pharmaceutically important interactions and can be drastically different from the material’s bulk properties. We first introduce current challenges in the surface and interface analysis of pharmaceutical materials in the context of material design, administration and fabrication. We then review recent scientific and technological advances aimed to address these issues and discuss examples that illustrate the capabilities of these techniques.