Levels Of Fidelity Research Articles

Exploring intensive care nurses' perception of simulation-based learning: A systematic review and meta-synthesis.

To explore intensive care nurses' (ICN) perceptions of simulation-based learning (SBL). A systematic review and meta-synthesis. The review followed the PRISMA guidelines for reporting a systematic review. A systematic search strategy was developed using a modified PICo framework. A comprehensive search was conducted in July 2023 in CINAHL, OVID Embase, Medline complete, Web of Science, ERIC and Scopus databases for articles published in English between 2013 and 2023. Data were extracted using the Joanna Briggs Institute QARI Data Extraction, with data synthesis guided by Braun and Clark's thematic analysis approach. Quality appraisal was assessed using the CASP tool. Eleven studies providing qualitative data were included for analysis. Analysis and meta-synthesis led to the construction of two themes: The learning experience and professional growth through collaboration. The review highlights the balance needed in finding the appropriate simulation approach, with the right level of fidelity, conducted at appropriately regular intervals, incorporating the correct makeup of professional team members, conducted in the right environment and facilitated by a skilled facilitator, to ensure best outcomes and return on investment for ICN's education. These findings are a valuable resource for educators and organisations considering simulation-based learning initiatives in the intensive care setting. This review involved analysis of existing literature and as such no unique patient or public involvement occurred. The systematic review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) reporting guidelines.

Not fully remembered, but not forgotten: interfering sounds worsen but do not eliminate the representation of pitch in working memory.

Recent research has begun measuring auditory working memory with a continuous adjustment task in which listeners adjust attributes of a sound to match a stimulus presented earlier. This approach captures auditory memory's continuous nature better than standard change detection paradigms that collect binary ("same or different") memory measurements. In two experiments, we assessed the impact of different interference stimuli (multitone complexes vs. white noise vs. silence) on the precision and accuracy of participants' reproductions of pitch from memory. Participants were presented with a target multitone complex stimulus followed by eight successive interference signals. Across trials, these signals alternated between additional multitone complexes, randomly generated white noise samples, or (in Experiment 2) silence. This was followed by a response period where participants adjusted the pitch of a response stimulus using a MIDI touchpad to match the target. Experiment 1 found a significant effect of interference type on performance, with tone interference signals producing the greatest impairments to participants' accuracy and precision compared to white noise. Interestingly, it also found a compression in the participants' responses, with overestimations of low-frequency targets and underestimations for high-frequency targets. Experiment 2 replicated results from Experiment 1, with an additional silence condition showing the best performance, suggesting that non-tonal signals also generate interference. In general, results support a shared resource model of working memory with a limited capacity that can be flexibly allocated to hold items in memory with varying levels of fidelity. Interference does not appear to knock items out of a fixed precision slot, but rather robs a portion of capacity from stored items.

Multi-fidelity physics constrained neural networks for dynamical systems

Physics-constrained neural networks are commonly employed to enhance prediction robustness compared to purely data-driven models, achieved through the inclusion of physical constraint losses during the model training process. However, one of the major challenges of physics-constrained neural networks consists of the training complexity especially for high-dimensional systems. In fact, conventional physics-constrained models rely on singular-fidelity data necessitating the assessment of physical constraints within high-dimensional fields, which introduces computational difficulties. Furthermore, due to the fixed input size of the neural networks, employing multi-fidelity training data can also be cumbersome. In this paper, we propose the Multi-Scale Physics-Constrained Neural Network (MSPCNN), which offers a novel methodology for incorporating data with different levels of fidelity into a unified latent space through a customised multi-fidelity autoencoder. Additionally, multiple decoders are concurrently trained to map latent representations of inputs into various fidelity physical spaces. As a result, during the training of predictive models, physical constraints can be evaluated within low-fidelity spaces, yielding a trade-off between training efficiency and accuracy. In addition, unlike conventional methods, MSPCNN also manages to employ multi-fidelity data to train the predictive model. We assess the performance of MSPCNN in two fluid dynamics problems, namely a two-dimensional Burgers’ system and a shallow water system. Numerical results clearly demonstrate the enhancement of prediction accuracy and noise robustness when introducing physical constraints in low-fidelity fields. On the other hand, as expected, the training complexity can be significantly reduced by computing physical constraint loss in the low-fidelity field rather than the high-fidelity one.

Assessing the validity of VR as a training tool for medical students

The advances in Virtual Reality technologies, increased availability and reducing hardware costs have diminished many of the early challenges in the adoption of VR. However, a commonly identified gap in immersive Virtual Reality-Head Mounded Display (VR-HMD) training for medical education is the confidence in the long-term validity of the applications, in particular, the acceleration of the learning curve efficacy of learning outcomes over time and actual skills translation into real environments. Research shows a wide range of ad hoc applications, with superficial evaluations often conducted by technology vendors, based on assumed environments and tasks, envisaged (as opposed to actual) users and effectiveness of learning outcomes underpinned with little or no research focusing on a requirements-driven validation approach. This presents decision-making challenges for those seeking to adopt, implement and embed such systems in teaching practice. The current paper aims to (i) determine whether medical VR training improves the skill acquisition of training candidates, (ii) determine the factors affecting the acquisition of skills and (iii) validate the VR-based training using requirement-driven approach. In this paper, we used within- and between-subject design approaches to assess the validity of VR-based surgical training platform developed by Vantari VR against requirements which have been identified to have impact on learning processes and outcomes in VR-based training. First, study and control groups were compared based on their level of skill acquisitions. Then, by tailoring a requirements framework, the system was validated against the appropriate requirements. In total, 74 out of 109 requirements were investigated and evaluated against survey, observer and stakeholder workshop data. The training scenario covered the topic of Arterial Blood Gas (ABG) collection for second-year university medical students. In total 44 students volunteered to participate in this study, having been randomly assigned to either the study or control group. Students exposed to VR training (the study group) outperformed the control group in practical clinical skills training tasks and also adhered to better safety and hygiene practices. The study group also had a greater procedural completion rate over the control group. Students showed increased self-efficacy and knowledge scores immediately post-VR training. Prior ABG training did not impact on VR training outcomes. Low levels of simulation sickness, physical strain and stress, coupled with high levels of enjoyability, engagement, presence and fidelity were identified as factors affecting the overall training experience. In terms of learning, high scores were recorded for active learning, cognitive benefit and reflective thinking. Lastly, by validating the system against 74 system requirements, the study found a user acceptance level of 75%. This enabled the identification of weaknesses of the current system and possible future directions.

Experimental and numerical analysis of the Microstructure and mechanical properties of unidirectional glass fiber reinforced epoxy composites

This paper proposes a numerical model to predict the pattern and features of the fracture surface and to understand the mechanisms and cause of the failure. Various fiber orientations of 0°, 90°, 0°/90° and ± 45° were utilized in the production of unidirectional glass-fiber-reinforced epoxy composites via the vacuum bagging technique. The mechanical properties of the manufactured composites were evaluated by measuring parameters including tensile strength, compressive strength, flexural strength and interlaminar shear strength. High-resolution scanning electron microscopy was used to examine the mechanisms of fracture in laminates. The mechanical properties of the composite material were found to be considerably improved when a unidirectional 0° fiber orientation was used, as compared to other fiber orientations. This was true for tensile, compressive, flexural and interlaminar shear loading modes. The composite laminates demonstrated several modes of breaking, including fibers pulling away from the matrix, holes in the matrix and river flow lines, depending on the direction of the fibers. The outcomes of the numerical simulation demonstrate a high level of fidelity with experimental findings. This study provides a valuable reference for predicting numerical analysis of the microstructure and mechanical properties.

In-house Extraction and Purification of Pfu-Sso7d, a High-processivity DNA Polymerase.

The polymerase chain reaction (PCR) is an extensively used technique to quickly and accurately make many copies of a specific segment of DNA. In addition to naturally existing DNA polymerases, PCR utilizes a range of genetically modified recombinant DNA polymerases, each characterized by varying levels of processivity and fidelity. Pfu-Sso7d, a fusion DNA polymerase, is obtained by the fusion of Sso7d, a small DNA-binding protein, with Pfu DNA polymerase. Pfu-Sso7d is known for its high processivity, efficiency, and fidelity but is sold at a sumptuously high price under various trade names and commercial variants. We recently reported a quick and easy purification protocol that utilizes ethanol or acetone to precipitate Pfu-Sso7d from heat-cleared lysates. We also optimized a PCR buffer solution that outperforms commercial buffers when used with Pfu-Sso7d. Here, we provide a step-by-step guide on how to purify recombinant Pfu-Sso7d. This purification protocol and the buffer system will offer researchers cost-efficient access to fusion polymerase. Key features • We detail a precipitation-based protocol utilizing ethanol and acetone for purifying Pfu-Sso7d. • Despite ethanol and acetone displaying effective precipitation efficiency, acetone is preferred for its superior performance. • Furthermore, we present a PCR buffer that outperforms commercially available PCR buffers. • The Pfu-Sso7d purified in-house and the described PCR buffer exhibit excellent performance in PCRapplications.

Stress, strain, neutron transport and radiation effects in a full fusion tokamak device: A virtual MAST-U study

A finite-element method (FEM) model for the Mega-Ampere Spherical Tokamak - Upgrade (MAST-U) fusion tokamak has been developed to evaluate stress and deformations in the full device structure and to assess the stability of the whole tokamak with respect to its simulated exposure to an artificial level of neutron irradiation. Here, we use MAST-U as a proxy for a fusion power plant to explore the level of fidelity made possible by modern supercomputing systems. Gravity and atmospheric pressure were used to test the high-resolution FEM model, involving in excess of 122 million elements. Taking the MASTU fusion plasma as a neutron source, we perform full-scale neutron transport calculations to quantify spatial variations in the neutron flux and assess the neutron radiation exposure across the structure. This is a first step towards applying recently developed multiscale computational tools to evaluate the spectrum of stress in the tokamak, identifying the location of stress concentrations as well as their magnitude. This study provides an example of full fusion device neutronics and FEM simulations which are enabling UKAEA to define computational requirements for modelling a whole fusion power plant as well as for specifying operating conditions for the relevant materials.

Cell behaviors that pattern developing tissues: the case of the vertebrate nervous system.

Morphogenesis from cells to tissue gives rise to the complex architectures that make our organs. How cells and their dynamic behavior are translated into functional spatial patterns is only starting to be understood. Recent advances in quantitative imaging revealed that, although highly heterogeneous, cellular behaviors make reproducible tissue patterns. Emerging evidence suggests that mechanisms of cellular coordination, intrinsic variability and plasticity are critical for robust pattern formation. While pattern development shows a high level of fidelity, tissue organization has undergone drastic changes throughout the course of evolution. In addition, alterations in cell behavior, if unregulated, can cause developmental malformations that disrupt function. Therefore, comparative studies of different species and of disease models offer a powerful approach for understanding how novel spatial configurations arise from variations in cell behavior and the fundamentals of successful pattern formation. In this chapter, I dive into the development of the vertebrate nervous system to explore efforts to dissect pattern formation beyond molecules, the emerging core principles and open questions.

Nest box occupancy dynamics by hazel dormice (Muscardinus avellanarius) in central-western Romania

The hazel dormouse, Muscardinus avellanarius is a vulnerable and protected species that is challenging to study due to its specific way of life. Limited data on its distribution and population parameters are available for Romania. We collected data regarding species’ biology and ecology in the hilly areas of central-western Romania, within deciduous forests dominated by oak or beech species. We regularly monitored 80 wooden nestboxes, which served as shelter and breeding sites for the species, to assess the seasonal and sex-related variations in nest box usage. The highest occupancy levels were observed during the autumn, with a smaller peak in the spring. Males occupied more nest boxes than females, although the difference was not statistically significant. They also travelled greater distances. Most nest boxes were occupied by a single individual at a time. Recapture rates did not differ significantly between males and females, and most individuals were recaptured only once. Hazel dormice showed a high level of site fidelity, often returning to the same nestbox or one nearby. Interestingly, 14% of the females bred twice a year, which is a lower percentage compared to findings from other studies. Nest box occupancy rates in this region were also lower than those reported in other areas. However, it is important to note that these variations may be attributed to differences in methodology. The occupancy rate declined with the increased presence of the larger species, the fat dormouse Glis glis, which outcompeted the hazel dormouse.

Clinical Simulation for Procedural Expertise: State of Education and Application

Procedural skills are a core component in the health care practice that extends across all medical practitioners, from novice trainees to specialists. Medical institutions have widely adopted simulation to develop the clinical and procedural skills of health profession students. This review evaluates the evidence regarding simulation-based training for developing procedural expertise among medical students and junior doctors. For this purpose, Google Scholar and MEDLINE/PubMed databases were searched for articles published on simulation-based procedural training between January 2000 and October 2023. Reviews or studies published in languages other than English and research that showed evidence on communication, critical thinking, teamwork, decision-making, and cognitive skills were excluded from the search. The focus was placed on clinical and psychomotor skills as this review intends to inform clinical skills teaching and research practice. The results reveal that simulation-based training has been utilized increasingly to train medical students and junior doctors in procedural skills. Varying levels of fidelity have been incorporated to train psychomotor skills about a multitude of common and rare procedures. The evidence supports the acquisition of knowledge and procedural skills via simulation. Evidence also supports the transfer of skills from the simulated environment to clinical practice and live patients. However, resource intensiveness has limited the implementation of this method of education in developing countries. When used consciously, simulation can complement clinical training to produce competent doctors capable of effective patient care.

Addressing the Patient Experience through Human- Centred Design: A Scoping Review

Background: There is an increasing interest in patient experience for improving the quality of services together with clinical effectiveness and patient safety. Human-Centred Design (HCD), (design thinking and service design) are design approaches that are increasingly used to propose new patient-centred solutions. However, the evidence on the relationship between HCD and patient experience is at an early stage.
 Objective: This study investigates the intersection between patient experience and HCD by focusing on patient-centred care models, HCD principles, and strategies.
 Methods: First, PRISMA was used for the scoping review which includes 45 articles that apply HCD to improve patient experience. Second, the articles were analysed following the PICOS (participants, intervention, output, study design) framework. Third, a qualitative analysis of the studies was performed following the ENTREQ method to identify patterns in the relationship between HCD and patient experience. We create a framework that defines design practices in terms of three strategies (understanding people, stakeholder involvement, and systems approach) and six principles (understand, involve, evaluate, iterate, holistic experience, and multidisciplinary team), intersecting with the eight patient experience dimensions (respect, coordination, information, comfort, emotional support, involvement, continuity, access). Main results: The use of HCD primarily addresses respect for patient preferences, coordination between professionals, adequate patient information and continuity of care. 91% of the solutions derived from HCD practices pursue an improved patient experience by respecting patient values. The HCD practices reviewed to date have a high level of fidelity with ISO 9241-210 principles (78%). The most commonly employed design strategy is the involvement of patients and stakeholders in the design process. Articles that have focused on patient involvement have best met the design principles. Conclusion: This study provides a holistic understanding of how HCD has been applied to date to address the patient experience. This research organises current knowledge, identifies the dimensions of patient experience that benefit most from the application of HCD and identifies the most commonly employed design activities. 
 Patient or Public Contribution: There has been no contribution in this research other than by the authors.

The Engaged Learners Program: Effects on Student Engagement During Small Group Reading Instruction.

In this study we tested the usability, feasibility, social validity, and effectiveness of Engaged Learners, a behavior support program designed to be integrated into small group reading interventions. Participants included eight Grade 3 to 5 students with co-occurring reading difficulties and inattention. A concurrent multiple-baseline design was utilized to test the effects of Engaged Learners on engagement outcomes. Visual analysis and effect sizes indicated an improvement in engagement for seven students. Interventionists and students viewed the Engaged Learners program to be effective and socially valid. Limitations included lower than expected levels of fidelity for one interventionist and high student absenteeism. More research is needed to identify the extent to which Engaged Learners can support reading outcomes. Educators seeking an effective behavior support program that requires minimal training and coaching may consider integrating Engaged Learners into their small group reading instruction.

High geometric fidelity through closed-loop control of the weld pool size in gas metal arc welding based direct energy deposition

Arc based direct energy deposition combines the flexibility of additive manufacturing with high build rates and low investment costs. However, high geometric fidelity of manufactured components is not possible with state-of-the-art methods. Highly varying and geometry-dependent boundary conditions, e.g. heat dissipation and the interpass temperature, are quasi-random influences with a strong impact on the geometric fidelity and the manufactured microstructure. Without adjusting for these variations, process stability decreases, geometric deviations become more likely and defects accumulate from layer to layer. A high geometric fidelity of the manufactured components can therefore not be guaranteed with the state of the art. Due to the large number of influencing variables in the arc-based manufacturing process, this problem cannot be solved by the definition of simple setpoints. Closed-loop control, however, offers the opportunity to flexibly counteract any deviations that occur by adjusting the process parameters in real time. Since the manufactured part is created by solidification from the weld pool, a closed-loop control of the weld pool size is being developed. The developed controller uses the weld pool properties and the interpass temperature as feedback variables and takes into account the non-linear system behaviour as well as the process noise and the parameter uncertainties. The subordinate control of the welding power source is further used for improved process stability. To the best of our knowledge, this solution provides a level of robustness, steady-state accuracy and geometric fidelity that has not been achieved by previous approaches reported in the literature. To illustrate the performance of this closed-loop control for components with low heat dissipation, we demonstrate the fabrication of thin-walled components with high geometric accuracy for a fast 3D printing process and investigate the influence of the welding process variables on the microstructure, the evaluation of the geometric fidelity is based on EN ISO 1101.

Extended Hierarchical Kriging Method for Aerodynamic Model Generation Incorporating Multiple Low-Fidelity Datasets

Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity (HF) samples with multiple low-fidelity (LF) datasets structured in hierarchical levels to generate a precise HF approximation model. However, challenges arise when dealing with non-level LF datasets, where the fidelity levels of LF models are indistinguishable across the design space. In such cases, conventional methods employing recursive frameworks may lead to inefficient LF dataset utilization and substantial computational costs. To address these challenges, this work proposes the extended hierarchical Kriging (EHK) method, designed to simultaneously incorporate multiple non-level LF datasets for improved HF model construction, regardless of minor differences in fidelity levels. This method leverages a unique Bayesian-based MFSM framework, simultaneously combining non-level LF models using scaling factors to construct a global trend model. During model processing, unknown scaling factors are implicitly estimated through hyperparameter optimization, resulting in minimal computational costs during model processing, regardless of the number of LF datasets integrated, while maintaining the necessary accuracy in the resulting HF model. The advantages of the proposed EHK method are validated against state-of-the-art MFSM methods through various analytical examples and an engineering case study involving the construction of an aerodynamic database for the KP-2 eVTOL aircraft under various flying conditions. The results demonstrated the superiority of the proposed method in terms of computational cost and accuracy when generating aerodynamic models from the given multi-fidelity datasets.

Non-myopic multipoint multifidelity Bayesian framework for multidisciplinary design

The adoption of high-fidelity models in multidisciplinary design optimization (MDO) permits to enhance the identification of superior design configurations, but would prohibitively rise the demand for computational resources and time. Multifidelity Bayesian Optimization (MFBO) efficiently combines information from multiple models at different levels of fidelity to accelerate the MDO procedure. State-of-the-art MFBO methods currently meet two major limitations: (i) the sequential adaptive sampling precludes parallel computations of high-fidelity models, and (ii) the search scheme measures the utility of new design evaluations only at the immediate next iteration. This paper proposes a Non-Myopic Multipoint Multifidelity Bayesian Optimization (NM3-BO) algorithm to sensitively accelerate MDO overcoming the limitations of standard methods. NM3-BO selects a batch of promising design configurations to be evaluated in parallel, and quantifies the expected long-term improvement of these designs at future steps of the optimization. Our learning scheme leverages an original acquisition function based on the combination of a two-step lookahead policy and a local penalization strategy to measure the future utility achieved evaluating multiple design configurations simultaneously. We observe that the proposed framework permits to sensitively accelerate the MDO of a space vehicle and outperforms popular algorithms.

Challenges of conducting a randomised placebo-controlled trial of spinal surgery: the SUcceSS trial of lumbar spine decompression

Although placebo-controlled trials are considered the gold standard for evaluating the efficacy of healthcare interventions, they can be perceived to be controversial and challenging to conduct for surgical treatments. The SUcceSS trial is the first placebo-controlled trial of lumbar decompression surgery for symptomatic lumbar canal stenosis. The SUcceSS trial has experienced common issues affecting the implementation of randomised placebo-controlled surgery trials, accentuated by the COVID-19 pandemic. Using the SUcceSS trial as an example, we discuss key challenges and mitigation strategies specific to the conduct of a randomised placebo-controlled surgical trial. Overall, the key lessons learned were (i) involving key stakeholders early and throughout the trial design phase may increase clinician and patient willingness to participate in a placebo-controlled trial of surgical interventions, (ii) additional resources (e.g. budget, staff time) are likely required to successfully operationalise trials of this nature, (iii) the level of placebo fidelity, timing of randomisation relative to intervention delivery, and nuances of the surgical procedure under investigation should be considered carefully. Findings are based on one example of a placebo-controlled surgical trial; however, researchers may benefit from employing or building from the strategies described and lessons learned when designing or implementing future trials of this nature.

Large eddy simulation-bivariate sectional model for non-spherical TiO2 nanoparticle synthesis in flame

Numerical simulation of nanoparticle synthesis in flame necessitates a high level of fidelity for turbulent flame, as well as delivers more detail insight into the evolution of structure and size distribution of particles undergoing various dynamic events. In the present work, a new simulation approach coupling large-eddy simulation (LES) and bivariate sectional model is proposed to explore the synthesis of nanoparticles in turbulent flame. More specifically, the nonlinear LES-partially stirred reactor model (NLES-PaSR) is utilized to simulate the turbulent flame, wherein the gradient-type structural subgrid-scale (SGS) model for turbulent flow and partially stirred reactor (PaSR) model for turbulent combustion are considered. In addition, the volume-based bivariate sectional model is thoroughly coupled with the LES model for the first time to describe the spatiotemporally resolved formation and growth of nanoparticles using particle number concentration and surface area concentration as two sets of variables. Compared directly with the LES-monodisperse (LES-Mono) and LES-univariate sectional (LES-UniSe) models, the LES-bivariate sectional (LES-BiSe) model has significant advantages in its ability to analyze and predict the size, morphology, as well as polydispersed particle size distribution (PSD) evolution of nanoparticles at a moderate computational cost simultaneously. In the LES framework, the proposed model successfully simulates the spatiotemporally resolved formation and growth of non-spherical TiO2 nanoparticle in turbulent diffusion burner. The predicted results derived from the LES-BiSe model are in good agreement with the experimental measurements. Also, the aggregate and primary particle size distribution shows highly temporal fluctuation, which mainly results from the continuous variations of particle path induced by the unsteady turbulent combustion. Furthermore, the present work demonstrates the profound dependence of particle morphological on both spatiotemporal evolution and their intrinsic size distribution. In particular, the large aggregates in the higher sections are commonly found as irregular structure with fractal-like dimensions.

The social behaviour of the common bottlenose dolphin Tursiops truncatus (Montagu, 1821) in the coastal waters of Lampedusa Island (Strait of Sicily, Italy)

Abstract Research on social structure and residency provides important information on the dynamics of a population, improving knowledge of the species' behaviour and ecology. This study investigated the social network, site fidelity, and residency patterns of common bottlenose dolphins (Tursiops truncatus) off Lampedusa Island. Direct visual detection and photo‐identification methods were used to collect data during 124 boat‐based surveys conducted from 2013 to 2020. A total of 117 groups (mean size 4.5 ± 3.3) were sighted; 73 well‐marked animals were identified, of which 59% were resighted over the years. The estimate of social differentiation was 0.72 (SE = 0.07), suggesting differentiated social groups within the community. Data were somewhat representative of the true social system, as the correlation coefficient was close to 0.4. However, the half‐weight index averaged 0.07 (±0.03), indicating individuals' low tendency to associate. Five social clusters were identified with strong relationships between individuals within each cluster, in which 94% of maximum association indices were ≥0.4. The data also highlighted preferred and avoided associations and stable relationships. The removal of individuals with the highest values of strength and eigenvector centrality from the network did not affect its connectivity, suggesting inherent robustness. Despite the different levels of site fidelity among individuals, the results indicated rather high levels of yearly sighting rate. Temporary migration into and out of the area shown by this study indicates that Lampedusa coastal waters are an important, regularly used bottlenose dolphin habitat. These results suggest extensive ranging behaviour, which implies the need for networking between institutions and organizations from the various states bordering the Strait of Sicily to address conservation efforts and inform regional management of the Mediterranean bottlenose dolphin population.

Predicting Take-Off Noise, Sonic Boom, and Landing Noise of Supersonic Transport Aircraft Concepts

In 2023, the German Aerospace Center (DLR) has launched the STORMIE (Supersonic Transport Open Research Models and Impact on Environment) project. Focus of the project is the prediction and minimization of environmental and human impacts of civil supersonic transport. Data generated in the project will be used to inform national and European authorities in order to discuss certification standards for supersonic aircraft within the International Civil Aviation Organization's Committee on Aviation Environmental Protection (CAEP). In order to assess the environmental impacts, representative civil supersonic business-jet and airliner concepts will be designed. This paper will present an overview of past and ongoing activities conducted at DLR to assess and minimize landing and take-off noise as well as the sonic boom of supersonic aircraft. Numerical methods at different levels of fidelity are applied and will be complemented by listening tests of auralized simulation data in a later project stage. First noise-related activities within the STORMIE project are summarized.

Process evaluation of the Invictus Pathways Program.

UniSA's Invictus Pathways Program (IPP), a service program, was originally developed to assist veterans to train for and participate in the Invictus Games. More recently, the scope of the IPP has widened to support and improve wellbeing and facilitate post traumatic growth and recovery among participants who are living with physical and mental health injuries and conditions. This paper describes the components of the IPP and reports its process evaluation. Underpinned by a pragmatic approach, data related to participant and student involvement in the IPP, the number of participant training sessions, session attendance, program activities and events, and program fidelity were compiled from process documentation that had been collected between 2017 and 2020, inclusive. Following ethics approval, semi-structured interviews were conducted with participants of the IPP, members of their family support network, and university staff to understand the operations of the IPP and satisfaction with the program. There was high fidelity for the student-led exercise training aspects of IPP; however, data collection relevant to participants' psychological outcomes, and non-training IPP events and activities did not always occur as intended. Between 2017 and 2020, 53 veterans had participated in or were still participating in the IPP, and 63 allied health students had completed placements as student trainers. Fifty-three individual training sessions were delivered in 2017, increasing to 1,024 in 2020. Seventy-one interviews were completed with key IPP stakeholders. The qualitative analysis identified four higher order themes: Implementation and fidelity of the IPP, Satisfaction with the IPP, Areas of the IPP requiring improvement and suggestions for change, and Sustainability of the IPP. Satisfaction was generally high for the IPP, although there were factors that negatively impacted the experience for some participants and their family support network. Suggestions for improvement to program components and delivery aspects were made during the interviews, and the precariousness of IPP funding and sustainability was raised as an ongoing concern. This process evaluation has demonstrated that the physical activity training components of the IPP were delivered with high levels of fidelity, and that satisfaction with the IPP is mostly high, although there are areas that could be improved. There is a need for a more structured approach to the ongoing evaluation of the IPP. This includes ensuring that program staff have a shared understanding of the purpose of evaluation activities and that these activities occur as intended. Beyond this is the need to secure funding to support the sustainability of the IPP, so that it can continue to contribute to the wellbeing of veterans living with physical and mental health conditions, and their families.