Levels Of Fidelity Research Articles

Exploring methods for generating synthetic data in Scotland to improve access to public sector data for research

Objective and ApproachWe are working to improve the economic, social and environmental wellbeing in Scotland by enabling access to and linkage of public-sector data for research in the public good. Our objective was to examine how synthetic data can support this aim by allowing researchers to test approaches and write code while awaiting the necessary permissions to use the real data. We have explored generating synthetic data from metadata and from actual data. ResultsThrough engagement, researchers expressed interest in low fidelity data, which minimises privacy and information governance risks. We have created low fidelity data from information provided by data controllers in publicly-available data dictionaries. We have also created more high-fidelity data based on actual data, using the synthpop tool. We are carrying out further work to engage with data controllers about the level of fidelity that is acceptable to them, as well as the information that needs to be included in the data dictionary to meet this in an automated way, and how we will share datasets with researchers. A key part of these considerations is the ability to link synthetic datasets and the impact that has on the fidelity of the data. Conclusions and ImplicationsWe will share our approaches, the limitations we have found in using metadata to create synthetic data, difficulties encountered in using the synthpop tool, engagement we have had from controllers and researchers, and the proposed way forward for synthetic data in Scotland.

Analysis of the aerothermal performance of modern commercial high-pressure turbine rotors using different levels of fidelity

In the field of design and optimization of sophisticated geometries such as film-cooled turbine blades of modern jet engines, Computational Fluid Dynamics (CFD) simulation is commonly employed. As the pursuit for higher turbine entry temperatures intensifies, it becomes crucial for computational analyses to offer accurate predictions of metal temperatures and heat transfer coefficients on these critical components. This study investigates the impact of key physical factors that characterize the operation of these components on the accuracy of the computational model. In particular, the effects of including the exchange of thermal energy between the fluid and solid domains, as well as modelling the unsteady interaction between the rotor and stator are studied. The research focuses on a fully featured one-and-a-half stage high-pressure turbine of a commercial jet engine, utilizing proprietary software for conducting 3D Reynolds-Averaged Navier-Stokes flow simulations. To model the fluid-solid thermal interaction, steady-state Conjugate Heat Transfer (CHT) simulations are performed. The CHT results are then compared with experimental data obtained from a thermal paint test, achieving good levels of agreement. Additionally, phase-lag simulations are executed under adiabatic-wall conditions to evaluate the influence of stator-rotor interaction on near-wall gas temperatures. This work shows that, by modelling the periodic unsteadiness at the stator-rotor interface with a phase-lag technique, the maximum near-wall gas temperature prediction is significantly increased, sometimes more than 100K, with respect to the steady-state model one. Findings from this work also suggest that simplified “strip” source terms used to model the presence of film cooling hole rows on the surface of a blade can be used with satisfactory accuracy only for nominal conditions. The mass flows delivered by each source strip should not be linearly scaled based on mainstream quantities for use in different conditions, but they should be recalculated from scratch for the new conditions.

Positive Behaviour Support is effective when implemented correctly: a response to “Restrictive practice – A pathway to elimination” (Spivakovsky, Steele, & Wadiwel, 2023)

Spivakovsky et al. (2023) questioned the effectiveness of Positive Behaviour Support as an intervention for reducing challenging behaviour and the use of restrictive practices as a behaviour management approach. This article responds to their critique. We argue that the literature supports the effectiveness of Positive Behaviour Support when it is properly implemented. As employees of a Positive Behaviour Support service provider, our position is also supported by our experience of the use of Positive Behaviour Support and its beneficial outcomes. To ensure a high level of fidelity in the implementation of Positive Behaviour Support, it needs to align with the elements that underpin Positive Behaviour Support (i.e., elements of applied behaviour analysis, person-centred practice, human rights, system change) rather than simply implementing Positive Behaviour Support to meet existing legislative requirements. In conclusion, when Positive Behaviour Support service provision and implementation in Australia is correctly aligned with the core components of Positive Behaviour Support, positive outcomes for people with disabilities, including a reduction in the use of restrictive practices, can be achieved.

Pivoting Training and Coaching for an Early Numeracy Intervention During COVID-19.

Early numeracy skills are vital for kindergarten students because they provide the foundation for acquiring mathematics skills in both kindergarten and subsequent years. Teacher support to intervene with kindergarteners at risk for poor mathematics learning outcomes is a promising approach to addressing this achievement gap. The current study replicates previous work on an established early numeracy intervention, ROOTS. In this instance, ROOTS uses remote professional development as a novel format for interventionist training support during the COVID-19 pandemic. Findings indicate that interventionists receiving remote support for implementing ROOTS found training and coaching acceptable and feasible. Remote training and coaching supported strong levels of implementation fidelity. Furthermore, children who received the ROOTS intervention outperformed their control group peers on post-test measures of mathematics achievement within a randomized controlled trial research design. Outcomes and implications for using remote professional development as a format for supporting educators in their use of early numeracy intervention programs are discussed within a pandemic-response context.

FSO2N3-Mediated On-DNA Diazo-Transfer Chemistry.

DNA-encoded library (DEL) is a powerful hit selection technique in both basic science and innovative drug discovery. In this study, we report a robust and straightforward DNA-compatible diazo-transfer reaction utilizing FSO2N3 as the diazo-transfer reagent in solution. This reaction demonstrates high conversions and facile operation while being metal-free and maintaining high levels of DNA fidelity. It is also compatible with a wide range of substrates, allowing for convenient access to both aliphatic and aromatic amines. Consequently, it will further enrich the DEL chemistry toolbox.

Expanding Access to 3D Technology in Plastic Surgery of the Breast: Validation of the iPhone Against the Vectra H2.

The iPhone (Apple Inc, Cupertino, California) contains a high-fidelity 3D-scanner and is widely distributed in the United States. Presently, 3D analysis of the breast necessitates ownership of cost-prohibitive cameras and software packages such as the Vectra system. We compared the accuracy of 3D photos of the breast obtained with the iPhone X 3D scanner against the Canfield Vectra H2 (Canfield Scientific Inc. Parsippany, NJ) in an effort to expand access to 3D technology in plastic surgery. Twenty breasts (n=20) were 3D-photographed with iPhone X and the Vectra H2 and compared with color map analysis and by measuring distances across the model between key anatomical landmarks. These distances included sternal notch to nipple (SN-N), mid-chest to nipple (M-N), nipple to mid-inframammary fold (N-IMF), and inframammary fold width (IMF). Statistical tests included the Bland-Altman Plot analysis. When comparing absolute differences in distances between key anatomical landmarks, the average discrepancy in measurements between iPhone and Vectra image pairs were the following: SN-N: 0.94mm, M-N: 0.70mm, N-IMF 0.81mm, and IMF 0.96mm. Colormap analysis demonstrated an average error of 1.53mm, mean of 0.53mm, and standard deviation of ±1.81mm. Bland-Altman Plot revealed a mean difference of 0.13mm and an agreement interval between -1.90 and 2.17mm. The iPhone is capable of capturing 3D-photographs with a high level of fidelity when compared to Vectra. 3D-scans obtained with the iPhone may be useful for planning nipple position, measuring the breast footprint, choosing implants, and performing other functions using 3D technology that are typically performed using the more expensive systems.

Isotope-based inferences of the trophic niche of short-finned pilot whales in the Webbnesia

Knowledge of predator-prey interactions is key in ecological studies and understanding ecosystem function, yet this is still poorly explored in the deep-sea environment. Carbon (δ13C: 13C/12C) and nitrogen (δ15N: 15N/14N) stable isotope ratios of a deep-diving species, the short-finned pilot whale (Globicephala macrorhynchus), were used to explore knowledge gaps on its ecological niche and foraging habitats in the Webbnesia marine ecoregion (Tenerife Island, n = 27 animals vs. Madeira, n = 31; 500 km apart) where animals display distinct levels of site fidelity. Specifically, we tested whether intraspecific isotopic variation results from differences between geographic areas (due to possible foraging plasticity between regions), sexes, and/or years (2015–2020) using Generalized Linear Models. In general, significant differences (p < 0.05) were found in the stable isotope profiles of pilot whales between the two archipelagos, which were also reflected in their isotopic niche. The higher mean and wider range of δ15N values in Tenerife suggest that pilot whales consume prey of higher trophic levels and more diverse than Madeira. The higher mean and wider range of δ13C values in Madeira suggest that in that island, pilot whales rely on prey from more diverse habitats. There was significant variation between some years, but not between sexes. Finally, we discuss pilot whales' foraging strategies worldwide and infer the reliance on benthic or benthopelagic food sources in the Webbnesia.

Initial promise of child-parent psychotherapy in reducing stress and postpartum depression among mothers experiencing homelessness: a feasibility and pilot study.

Mothers experiencing homelessness undergo significant stressors in addition to parenting stress, yet the rate and treatment of postpartum depression (PPD) within this population has yet to be explored. We assessed the risk for PPD and examined the changes in PDD and parenting stress following engagement in treatment. Participants included 182 mothers with infants 7 months of age or younger in a shelter setting. After initial assessment of PPD and parenting stress, families participated in Child-Parent Psychotherapy (CPP). Post assessment was then conducted after 16 weeks. CPP was successfully implemented with high levels of procedural and content fidelity (M = 0.99, SD = 0.04; M = 0.95, SD = 0.09, respectively), treatment satisfaction (94%; M = 4.83, SD = 0.52), and relatively moderate levels of intervention completion (53.8%). Following participation in CPP, mothers reported decreases in parenting stress (d = 0.51) and continuous PPD symptom severity (d = 0.43). The proportion of mothers with clinically elevated self-report PPD symptoms also decreased from 15.3 to 6.7% (p = .013). Lastly, improvements in total parenting stress predicted improvements in PPD symptom severity (B = 0.12, p < .001). The findings highlight the relevance of screening for PPD among mothers experiencing homelessness. Most importantly, relationship-based interventions like CPP demonstrate promise in indirectly treating PPD for at-risk populations and within a shelter setting.

Long-term co-occurrence and gregariousness in the migratory common stingray using network analysis

Aggregations and social interactions play an important role in the movement ecology of many animals, including elasmobranchs. Several of these species have shown the capability of carrying out complex social behaviours, and the importance of sociality in this taxon is being realized. Although it is a growing field of study in the case of these organisms, these processes still need to be better understood, especially to support management and conservation policies. In this study, a long-term acoustic telemetry data set collected on Dasyatis pastinaca in a coastal marine protected area was analysed. A co-occurrence network analysis was done to investigate preferential associations among individuals, revealing non-random associations among them. The analysis revealed a few strong and consistent associations that were maintained across inter-migratory periods, as this species performs seasonal migrations to a nearby estuary, suggesting temporal stability of the observed associations. Moreover, individuals had similar average positions and a generally high overlap of space use in both periods, indicating some level of site fidelity to the fully protected area. Groups of up to 64% of tagged individuals were co-detected at a same receiver, particularly in the western side of the array. Despite our limited sample size, likely underestimating associations, these results show that in addition to their large-scale movement pattern, D. pastinaca is likely to also present active partner preference and spatial structure at a finer spatial scale. The nature of such results is relevant to support the protection of these species.

Using formative process evaluation to improve program implementation and accessibility of competitive group-based physical activity in the TEAM-PA trial

BackgroundThis study demonstrates how formative process evaluation was used to assess implementation and improve dose and fidelity in the Together Everyone Achieves More Physical Activity (TEAM-PA) randomized controlled trial. TEAM-PA uses a randomized group cohort design to evaluate the efficacy of a group-based intervention for increasing physical activity among African American women.MethodsIntervention groups met for 10 weeks and were co-led by female African American facilitators, with intervention sessions consisting of group feedback, a health curriculum, group-based physical activity games, and group-based goal-setting. Drawing from a multi-theoretical framework, the intervention targeted social affiliation using collaborative and competitive group strategies, including essential elements focused on group-based behavioral skills, peer-to-peer positive communication, collectivism, optimal challenge, social facilitation, and peer to peer challenges. Formative process evaluation was used to monitor reach, dose, and fidelity, and implement feedback and solutions.ResultsAcross two cohorts, four groups (n = 54) were randomized to the TEAM-PA intervention. On average 84.8% of participants attended each week, which exceeded the a priori criteria. Results from the systematic observations indicated that on average 93% of the dose items were completed in each session and adequate levels of fidelity were achieved at both the facilitator and group-levels. Participants were compliant with wearing the FitBits (6.73 ± 0.42 days/week) and most participants successfully contributed to meeting the group-based goals. The use of open-ended items also revealed the need for additional modifications to the group-based PA games, including allowing for individuals to take breaks, incorporating a broader range of exercises, minimizing activities that required bending/reaching down without assistance, and providing facilitators with additional training for implementing the games. Initial evidence suggests that these changes were successful in increasing participants’ comprehension of the games from Cohort 1 (M = 1.83, SD = 0.71) to Cohort 2 (M = 3.33, SD = 0.69).ConclusionFindings from this study demonstrated high levels of reach, dose, and fidelity, while also highlighting strategies for implementing competitive group-based PA games that are accessible across physical fitness levels. Formative process evaluation, including open-ended items and collaborative brainstorming, holds tremendous potential for improving future interventions.Trial registrationThis study was registered on Clinicaltrials.gov (# NCT05519696) on August 22, 2022 prior to the enrollment of the first participant on September 12, 2022 (https://clinicaltrials.gov/study/NCT05519696?term=NCT05519696&rank=1).

Patient responsiveness as a safewards fidelity indicator: a qualitative interview study on an acute psychiatric in-patient ward

BackgroundThe Safewards model aims to reduce conflict and use of containment on psychiatric wards. To evaluate the implementation of Safewards and understand why it is effective in some settings but not in others, it is important to assess the level of implementation fidelity. To do this, the Safewards Fidelity Checklist (SFC) is often used, which focuses on objective visual observations of interventions but does not include patient responsiveness. The latter is a key indicator of implementation fidelity and includes engagement, relevance, acceptability and usefulness. The aim of the present study was to investigate the fidelity of Safewards implementation on an acute psychiatric ward from the perspective of patient responsiveness.MethodThe study was conducted on a ward for patients with mainly affective disorders. To assess the general level of fidelity the SFC was used together with a detailed ward walkthrough. Ten patients were interviewed with a focus on patient responsiveness to each of the seven interventions implemented on the ward. Data were analysed using qualitative descriptive analysis.ResultsThe findings indicate high implementation fidelity, which was reflected in the SFC assessment, walkthrough and patient responsiveness. Patients gave examples of improvements that had happened over time or of the ward being better than other wards. They felt respected, less alone, hopeful and safe. They also described supporting fellow patients and taking responsibility for the ward climate. However, some patients were unfamiliar with a ward where so much communication was expected. Several suggestions were made about improving Safewards.ConclusionsThis study confirms previous research that patient responsiveness is an important factor for achieving fidelity in a prevention programme. The patients’ descriptions of the acceptability, relevance and usefulness of the specific interventions reflected to a high degree the objective visual observations made by means of the SFC and ward walkthrough. Patient engagement was demonstrated by several suggestions about how to adapt the interventions. There is potential to obtain valuable input from patients when adapting Safewards in practice. This study also presents many examples of practical work with these interventions and the effects it can have on patients’ experiences of care.

Ultra-low frequency noise external cavity diode laser systems for quantum applications

We present two distinct ultra-low frequency noise lasers at 729 nm with a fast frequency noise of 30 Hz2/Hz, corresponding to a Lorentzian linewidth of 0.1 kHz. The characteristics of both lasers, which are based on different types of laser diodes, are investigated using experimental and theoretical analysis with a focus on identifying the advantages and disadvantages of each type of system. Specifically, we study the differences and similarities in mode behavior while tuning frequency noise and linewidth reduction. Furthermore, we demonstrate the locking capability of these systems on medium-finesse cavities. The results provide insights into the unique operational characteristics of these ultra-low noise lasers and their potential applications in quantum technology that require high levels of control fidelity.

Multifidelity graph neural networks for efficient and accurate mesh‐based partial differential equations surrogate modeling

AbstractAccurately predicting the dynamics of complex systems governed by partial differential equations (PDEs) is crucial in various applications. Traditional numerical methods such as finite element methods (FEMs) offer precision but are resource‐intensive, particularly at high mesh resolutions. Machine learning–based surrogate models, including graph neural networks (GNNs), present viable alternatives by reducing computation times. However, their accuracy is significantly contingent on the availability of substantial high‐fidelity training data. This paper presents innovative multifidelity GNN (MFGNN) frameworks that efficiently combine low‐fidelity and high‐fidelity data to train more accurate surrogate models for mesh‐based PDE simulations, while reducing training computational cost. The proposed methods capitalize on the strengths of GNNs to manage complex geometries across different fidelity levels. Incorporating a hierarchical learning strategy and curriculum learning techniques, the proposed models significantly reduce computational demands and improve the robustness and generalizability of the results. Extensive validations across various simulation tasks show that the MFGNN frameworks surpass traditional single‐fidelity GNN models. The proposed approaches, hence, provide a scalable and practical solution for conducting detailed computational analyses where traditional high‐fidelity simulations are time‐consuming.

Multifidelity Methodology for Reduced-Order Models with High-Dimensional Inputs

In the early stages of aerospace design, reduced-order models (ROMs) are crucial for minimizing computational costs associated with using physics-rich field information in many-query scenarios requiring multiple evaluations. The intricacy of aerospace design demands the use of high-dimensional design spaces to capture detailed features and design variability accurately. However, these spaces introduce significant challenges, including the curse of dimensionality, which stems from both high-dimensional inputs and outputs necessitating substantial training data and computational effort. To address these complexities, this study introduces a novel multifidelity, parametric, and nonintrusive ROM framework designed for high-dimensional contexts. It integrates machine learning techniques for manifold alignment and dimension reduction—employing proper orthogonal decomposition and model-based active subspace—with multifidelity regression for ROM construction. Our approach is validated through two test cases: the 2D RAE 2822 airfoil and the 3D NASA CRM wing, assessing various fidelity levels, training data ratios, and sample sizes. Compared to the single-fidelity principal component–active subspace (PCAS) method, our multifidelity solution offers improved cost-accuracy benefits and achieves better predictive accuracy with reduced computational demands. Moreover, our methodology outperforms the manifold-aligned ROM method by 50% in handling scenarios with large input dimensions, underscoring its efficacy in addressing the complex challenges of aerospace design.

Implementation fidelity of intravenous ferric carboxymaltose administration for iron deficiency anaemia in pregnancy: a mixed-methods study nested in a clinical trial in Nigeria

BackgroundIron deficiency anaemia is common among pregnant women in Nigeria. The standard treatment is oral iron therapy, which can be sub-optimal due to side effects. Intravenous ferric carboxymaltose (FCM) is an evidenced-based alternative treatment with a more favourable side effect profile requiring administration according to a standardized protocol. In this study, we assessed the fidelity of administering a single dose of FCM according to protocol and identified factors influencing implementation fidelity.MethodsWe used a mixed-method approach with a sequential explanatory design nested in a clinical trial across 11 facilities in Lagos and Kano States, Nigeria. Guided by a conceptual framework of implementation fidelity, we quantitatively assessed adherence to protocol by directly observing every alternate FCM administration, using an intervention procedure checklist, and compared median adherence by facility and state. Qualitative fidelity assessment was conducted via in-depth interviews with 14 skilled health personnel (SHP) from nine purposively selected health facilities, using a semi-structured interview guide. We analyzed quantitative data using descriptive and inferential statistics in Stata and used thematic analysis to analyze the transcribed interviews in NVivo.ResultsA total of 254 FCM administrations were observed across the 11 study sites, with the majority in secondary (63%), followed by primary healthcare facilities (PHCs) (30%). Overall, adherence to FCM administration as per protocol was moderate (63%) and varied depending on facility level. The lowest level of adherence was observed in PHCs (36%). Median, adherence level showed significant differences by facility level (p = 0.001) but not by state (p = 0.889). Teamwork and availability of protocols are facilitation strategies that contributed to high fidelity. However, institutional/ logistical barriers are contextual factors that influenced the varied fidelity levels observed in some facilities.ConclusionsCollaborative teams and access to operating protocols resulted in high fidelity in some facilities. However, in some PHCs, fidelity to FCM was low due to contextual factors and intervention complexities, thereby influencing the quality of delivery. In Nigeria, scale-up of FCM will require attention to staff strength, teamwork and availability of administration protocols, in order to optimize its impact on anaemia in pregnancy.

Benchmarking of Aerodynamic Models for Isolated Propellers Operating at Positive and Negative Thrust

Operating a conventional propeller at negative thrust results in the operation of positively cambered blade sections at negative angles of attack, leading to flow separation. Consequently, accurately simulating the aerodynamics of propellers operating at negative thrust poses a greater challenge than at positive thrust. This study offers a comprehensive assessment of the aerodynamic modeling capabilities of numerical methods, spanning low to high fidelity, for computing propeller performance across both positive and negative thrust regimes. Low-fidelity methods, namely, blade-element momentum and lifting line theories, effectively predict propeller performance trends at positive thrust. However, they fail to capture trends at negative thrust beyond the maximum power output point due to the neglect of three-dimensional flow effects. Both steady and unsteady Reynolds-averaged Navier–Stokes (RANS) simulations with y+<1 perform well across both positive and negative thrust conditions, with errors below 2% for both thrust and power magnitudes near the maximum power output point. Lattice-Boltzmann very-large-eddy simulations (LB-VLESs) with y+≤10 exhibit excellent agreement with experimental data with less than 1% error near the maximum power output point but with significant computational costs. Conversely, LB-VLESs with y+≥15 offer a more economical approach to capture general trends with the computational cost of the same order as unsteady RANS. However, wall models introduce errors in modeling flow separation, leading to a 16% overestimation of power magnitude near the maximum power output point. The results highlight the necessity of using tools with increased fidelity levels when considering propeller operation at negative thrust compared to the conventional positive thrust regime.

Value of abstraction in performance assessment – When is a higher level of detail necessary?

In this study, different approaches in performance assessment (PA) of the long-term safety of a repository for radioactive waste were examined. This investigation was carried out as part of the DECOVALEX-2023 project, an international collaborative effort for research and model comparison. One specific task of the DECOVALEX-2023 project was the Salt Performance Assessment Modelling task (Salt PA), which aimed at comparing various models and methods employed in the performance assessment of deep geological repositories in salt. In the context of the Salt PA task, three distinct teams from SNL (United States), Quintessa Ltd (United Kingdom), and GRS (Germany) examined the consequences of employing different levels of abstractions when modelling the repository's geometry and implementing various features and processes, using the example of a simple hypothetical repository structure in domal salt. Each team applied their own tools: PFLOTRAN (SNL), QPAC (Quintessa) and LOPOS (GRS). These differ essentially regarding numerical concept and degree of detail in the representation of the underlying physical processes. The discussion focused on when simplifications can be appropriately applied and what consequences result from them. Furthermore, it was explored when and if a higher level of fidelity in geometry or physical processes is required.

A novel multi-fidelity optimization framework for high-altitude propellers

A novel optimization methodology is presented for optimizing high-altitude propellers operating in the lower stratosphere. The proposed methodology combines a Bayesian optimization approach for most design variables and Vortex Theory for the optimization of twist distribution and rotational velocity. For the Bayesian optimization part of the problem, a multi-fidelity approach is employed with three levels of modeling fidelity. The considered fidelity levels, from lower to higher, are: Vortex Theory, and 3D Reynolds-Averaged Navier-Stokes (RANS) with the use of γ−Reθ transition model, converged with first-order upwind, and second-order upwind for the momentum equations. Additionally, the optimization problem involves two objectives: maximizing the cruise efficiency and minimizing the total volume of the propeller. To enhance the performance of multi-fidelity, multi-objective (MFMO) acquisition functions, a novel algorithm is proposed. The proposed optimization methodology demonstrates its effectiveness in generating several high-performing propeller designs and proves to be more efficient than an equivalent problem formulation relying solely on Bayesian optimization. Post-processing of optimization data reveals new design variable bounds that correspond to more efficient blade shapes. These findings provide insights into some important geometric features of high-altitude propellers and establish guidelines for future optimization efforts within the specified thrust and power consumption ranges. Finally, simulations of the best-performing designs across a range of advance ratios and altitudes confirm their high performance in various operating conditions.

Designer cellular spheroids with DNA origami for drug screening.

Current in vitro models struggle to balance the complexity of human diseases with suitability for large-scale drug tests. While 3D cultures simulate human tissues, they lack cellular intricacy, and integrating these models with high-throughput drug screening remains a challenge. Here, we introduce a method that uses self-assembling nucleic acid nanostructures decorated living cells, termed NACs, to create spheroids with a customizable 3D layout. To demonstrate its uniqueness, our method effectively creates designer 3D spheroids by combining parenchymal cells, stromal cells, and immune cells, leading to heightened physiological relevance and detailed modeling of complex chronic diseases and immune-stromal interactions. Our approach achieves a high level of biological fidelity while being standardized and straightforward to construct with the potential for large-scale drug discovery applications. By merging the precision of DNA nanotechnology with advanced cell culture techniques, we are streamlining human-centric models, striking a balance between complexity and standardization, to boost drug screening efficiency.

Joining SUMO and Unreal Engine to Create a Bespoke 360 Degree Narrow Passage Driving Simulator

The use of simulators is widespread in driver behavioural research. The ability of driving simulators to achieve the high levels of behavioural fidelity desired by behavioural researchers is argued to be resultant of the physical fidelity of the simulator. Whilst attempts to maximise the physical fidelity of simulators have often been focused on the hardware capabilities of the simulator, the software of the simulator has been argued to be as important. This is because the software of a simulator controls the intelligence and the heterogeneity of the behaviours of the simulated vehicles, as well as the quality of the graphics of the simulation. Despite the importance of intelligent simulated agents, previous driving simulator studies have tended to simplify the behaviours of simulated vehicles and the scenarios that are presented to participants. This is particularly true of simulator studies investigating the decision-making of drivers at narrow passages, a relatively unregulated but hazardous situation in which two opposing vehicles must negotiate how to safely pass through a road narrowing, in which the interactive nature of the interaction has often been neglected. Following a review of the requirements for a representative narrow passage driving simulator, it is argued that co-simulation, an approach which combines multiple simulator types to create a global simulation, provides the best approach to creating intelligent simulated agents within an immersive environment for narrow passage behavioural research. As such, the development of a simulator for narrow passage behavioural research that combines SUMO and Unreal Engine is described. In particular, the development of a novel narrow passage behavioural model within SUMO that utilises previous behavioural findings is highlighted. To this end, it is argued that this approach facilitates higher levels of behavioural fidelity for narrow passage interaction studies and provides a framework for the investigation of other driver behaviours.