This study explored mental workload recognition methods for carrier-based aircraft pilots utilising multiple sensor physiological signal fusion and portable devices. A simulation carrier-based aircraft flight experiment was designed, and subjective mental workload scores and electroencephalogram (EEG) and photoplethysmogram (PPG) signals from six pilot cadets were collected using NASA Task Load Index (NASA-TLX) and portable devices. The subjective scores of the pilots in three flight phases were used to label the data into three mental workload levels. Features from the physiological signals were extracted, and the interrelations between mental workload and physiological indicators were evaluated. Machine learning and deep learning algorithms were used to classify the pilots’ mental workload. The performances of the single-modal method and multimodal fusion methods were investigated. The results showed that the multimodal fusion methods outperformed the single-modal methods, achieving higher accuracy, precision, recall and F1 score. Among all the classifiers, the random forest classifier with feature-level fusion obtained the best results, with an accuracy of 97.69%, precision of 98.08%, recall of 96.98% and F1 score of 97.44%. The findings of this study demonstrate the effectiveness and feasibility of the proposed method, offering insights into mental workload management and the enhancement of flight safety for carrier-based aircraft pilots.

The First Large Absorption Survey in H i (FLASH) is a large-area radio survey for neutral hydrogen in and around galaxies in the intermediate redshift range 0.4 < z < 1.0, using the 21-cm H i absorption line as a probe of cold neutral gas. The survey uses the ASKAP radio telescope and will cover 24,000 deg2 of sky over the next five years. FLASH breaks new ground in two ways – it is the first large H i absorption survey to be carried out without any optical preselection of targets, and we use an automated Bayesian line-finding tool to search through large datasets and assign a statistical significance to potential line detections. Two Pilot Surveys, covering around 3000 deg2 of sky, were carried out in 2019-22 to test and verify the strategy for the full FLASH survey. The processed data products from these Pilot Surveys (spectral-line cubes, continuum images, and catalogues) are public and available online. In this paper, we describe the FLASH spectral-line and continuum data products and discuss the quality of the H i spectra and the completeness of our automated line search. Finally, we present a set of 30 new H i absorption lines that were robustly detected in the Pilot Surveys, almost doubling the number of known H i absorption systems at 0.4 < z < 1. The detected lines span a wide range in H i optical depth, including three lines with a peak optical depth τ > 1, and appear to be a mixture of intervening and associated systems. Interestingly, around two-thirds of the lines found in this untargeted sample are detected against sources with a peaked-spectrum radio continuum, which are only a minor (5-20%) fraction of the overall radio-source population. The detection rate for H i absorption lines in the Pilot Surveys (0.3 to 0.5 lines per 40 deg2 ASKAP field) is a factor of two below the expected value. One possible reason for this is the presence of a range of spectral-line artefacts in the Pilot Survey data that have now been mitigated and are not expected to recur in the full FLASH survey. A future paper in this series will discuss the host galaxies of the H i absorption systems identified here.

We present the first results of a pilot ‘TASmanian Search for Inclined Exoplanets’ (TASSIE) program. This includes observations and analysis of five short-period exoplanet candidates using data from TESS and the Harlingten 50 cm telescope at the Greenhill Observatory. We describe the instrumentation, data reduction process and target selection strategy for the program. We utilise archival multi-band photometry and new mid-resolution spectra to determine stellar parameters for five TESS Objects of Interest (TOIs). We then perform a statistical validation to rule out false positives, before moving on to a joint transit analysis of the remaining systems. We find that TOI3070, TOI3124 and TOI4266 are likely non-planetary signals, which we attribute to either short-period binary stars on grazing orbits or stellar spots. For TOI3097, we find a hot sub-Jovian to Jovian size planet (R3097Ab = 0.89 ± 0.04 RJ, P3097Ab = 1.368386 ± 0.000006 days) orbiting the primary K dwarf star in a wide binary system. This system shows indications of low metallicity ([Fe/H] ≈ −1), making it an unlikely host for a giant planet. For TOI3163, we find a Jovian-size companion on a circular orbit around a late F dwarf star, with R3163b = 1.42 ± 0.05RJ and P3163b = 3.074966 ± 0.000022 days. In future, we aim to validate further southern giant planet candidates with a particular focus on those residing in the sub-Jovian desert/savanna.

The Australian SKA Pathfinder (ASKAP) offers powerful new capabilities for studying the polarised and magnetised Universe at radio wavelengths. In this paper, we introduce the Polarisation Sky Survey of the Universe’s Magnetism (POSSUM), a groundbreaking survey with three primary objectives: (1) to create a comprehensive Faraday rotation measure (RM) grid of up to one million compact extragalactic sources across the southern ∼ 50 per cent of the sky (20,630 deg2); (2) to map the intrinsic polarisation and RM properties of a wide range of discrete extragalactic and Galactic objects over the same area; and (3) to contribute interferometric data with excellent surface brightness sensitivity, which can be combined with single-dish data to study the diffuse Galactic interstellar medium. Observations for the full POSSUM survey commenced in May 2023 and are expected to conclude by mid-2028. POSSUM will achieve an RM grid density of around 30–50 RMs per square degree with a median measurement uncertainty of ∼1 rad m−2. The survey operates primarily over a frequency range of 800–1088 MHz, with an angular resolution of 20″ and a typical RMS sensitivity in Stokes Q or U of 18 μJy beam−1. Additionally, the survey will be supplemented by similar observations covering 1296–1440 MHz over 38 per cent of the sky. POSSUM will enable the discovery and detailed investigation of magnetized phenomena in a wide range of cosmic environments, including the intergalactic medium and cosmic web, galaxy clusters and groups, active galactic nuclei and radio galaxies, the Magellanic System and other nearby galaxies, galaxy halos and the circumgalactic medium, and the magnetic structure of the Milky Way across a very wide range of scales, as well as the interplay between these components. This paper reviews the current science case developed by the POSSUM Collaboration and provides an overview of POSSUM’s observations, data processing, outputs, and its complementarity with other radio and multi-wavelength surveys, including future work with the SKA.

The kinetic stability of collisionless, sloshing beam-ion ($45^\circ$ pitch angle) plasma is studied in a three-dimensional (3-D) simple magnetic mirror, mimicking the Wisconsin high-temperature superconductor axisymmetric mirror experiment. The collisional Fokker–Planck code CQL3D-m provides a slowing-down beam-ion distribution to initialize the kinetic-ion/fluid-electron code Hybrid-VPIC, which then simulates free plasma decay without external heating or fuelling. Over $1$–$10\;\mathrm{\unicode{x03BC} s}$, drift-cyclotron loss-cone (DCLC) modes grow and saturate in amplitude. The DCLC scatters ions to a marginally stable distribution with gas-dynamic rather than classical-mirror confinement. Sloshing ions can trap cool (low-energy) ions in an electrostatic potential well to stabilize DCLC, but DCLC itself does not scatter sloshing beam-ions into the said well. Instead, cool ions must come from external sources such as charge-exchange collisions with a low-density neutral population. Manually adding cool $\mathord {\sim } 1\;\mathrm{keV}$ ions improves beam-ion confinement several-fold in Hybrid-VPIC simulations, which qualitatively corroborates prior measurements from real mirror devices with sloshing ions.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Diversifying the simplified landscape of corn and soybeans in the Midwest is an emerging priority in both the public and private sectors to reap a suite of climate, social, agronomic, and economic benefits. However, little research has documented the perspectives of farmers, the primary stakeholders in diversification efforts. This preliminary report uses newly collected survey data (n = 725) from farmers in the states of Illinois, Indiana, and Iowa to provide descriptive statistics and tests to understand what farmers in the region think about agricultural diversification, including their perspectives on its benefits, barriers, and opportunities. For the purposes of the study, we define diversification as extended rotations, perennials, horticulture, grazed livestock, and agroforestry practices. We find that a majority or plurality of farmers in the sample believe that diversified systems are superior to non-diversified systems at achieving a range of environmental, agronomic, and economic goals, although many farmers are still forming opinions. Farmers believe that primarily economic barriers stand in the way of diversification, including the lack of affordable land, low short-term returns on investment, and lack of labor. Farmers identified key opportunities to increase diversification through developing processing capacity for local meat and specialty crops, increasing demand for diversified products, and providing more information on returns on investment of diversified systems. Different interventions, however, may be needed to support farmers who are already diversified compared to non-diversified farmers. Building on these initial results, future studies using these data will develop more detailed analyses and recommendations for policymakers, the private sector, and agricultural organizations to support diversification.

Urinary tract infections (UTI) are amongst the most common bacterial infections worldwide, posing significant clinical and economic burden(1). Women are more susceptible, with nearly 50–60% of women experiencing at least one UTI during their lifetime, and 30–40% experiencing recurrent UTI (rUTI) in their lifetime(1). Cystitis, the most common UTI, remains one of the most common indications for prescribing antimicrobial treatment. However, continued use is associated with antimicrobial resistance(2), a major concern to health care and economic burden. Establishing alternative safe and effective non-antibiotic therapies for prevention of rUTI in otherwise healthy women is therefore important. Cranberry-containing products have been shown to reduce risk of UTIs(3) through inducing anti-adhesive activity against uropathogenic Escherichia coli to uroepithelial cells(4). Most clinical trials to date have tested fractions from cranberry fruit, such as juice concentrate or isolated proanthocyanidins(3). This study investigated the effect of a whole cranberry fruit powder supplement on incidence of culture-confirmed UTI (primary outcome) in women with rUTI history. A multicentre, 6-month, randomised, placebo-controlled, double-blind study enrolled 150 healthy females (18–65 years, body mass index (BMI) > 17.5-<35 kg/m2) with rUTI. rUTI was defined as ≥ 3 UTIs in the last year or at least 2 UTIs in the last 6 months, confirmed by a health professional. Women with a history of > 5 UTIs in the last 6 months were excluded. Eligible participants were randomised to 1 capsule of either 500 mg/day whole cranberry powder (Swisse High Strength Cranberry [Pacran®]) or placebo. Culture-confirmed UTIs (> 108 cfu/L) from mid-stream urine samples were assessed throughout the intervention period whenever participants experienced UTI symptoms (including dysuria, urinary frequency or urgency, fever, suprapubic pain, or macroscopic haematuria), and at baseline, 3- and 6-month clinic visits. Whole cranberry powder reduced culture-confirmed UTI risk compared to placebo by 52% (adjusted relative risk [RR] = 0.48, 95% CI = [0.26, 0.87], p = 0.01); reduced Escherichia coli UTIs (RR = 0.49, 95% CI = [0.24, 1.01], p = 0.05); incidence of UTI with urinary frequency and urgency symptomatology (RR = 0.29, 95% CI = [0.13, 0.63], p < 0.01); delayed time to first UTI episode (adjusted hazard ratio [HR] = 0.36, 95% CI = [0.18, 0.74], p = 0.01); and reduced the mean total number of UTIs per participant (adjusted incidence rate ratio [IRR] = 0.41, 95% CI = [0.21, 0.79], p = 0.01). Differences between groups in incidence of symptomatic suspected UTIs, and culture-confirmed dysuria were not detected. No safety concerns were reported. In conclusion, this study provides robust evidence that whole cranberry powder is safe to consume and reduces the incidence of culture-confirmed UTI and several other UTI-related outcomes in healthy women with rUTI history.

Emerging research has highlighted a relationship between diet and genetics, suggesting that individuals may benefit more from personalised dietary recommendations based on their genetic risk for cardiovascular disease (CVD)(1,2). This current study aims to: (1) Measure knowledge of genetics among healthcare professionals (HCPs) working in CVD, (2) Identify HCPs’ attitudes to using genetic risk to tailor dietary interventions, and (3) Identify perceived barriers and enablers to implementing genetics to tailor dietary interventions. In a mixed-methods study, Australian HCPs (dietitians and AHPRA registered healthcare professionals) working with people with CVD were invited to complete an anonymous online survey (REDCap) and an optional interview. Recruitment occurred through social media and relevant professional organisations. Survey questions were underpinned by the theoretical domains framework(3) and data was synthesised descriptively. Semi-structured interviews were undertaken via Zoom. Interview responses were analysed using a thematic analysis approach using Braun & Clarke methodology(4). Survey responders (n = 63, 89% female, mean age 42 ± 14 years) were primarily dietitians (83%), with ≥ 10 years of experience (56%) and spent at least 20% of their time working with people with CVD (n = 55, 87%). Approximately half of respondents were aware that genetic testing for CVD exists (n = 36) and always assess family history of CVD (n = 31). Few respondents reported using genetic testing (n = 5, 8%) or felt confident interpreting and using genetic testing (n = 7, 11%) in practice. Respondents were interested in incorporating genetics into their practice to tailor dietary advice (n = 44, 70%). Primary barriers to using genetic testing included financial costs to patients and negative implications for some patients. Almost all respondents agreed genetic testing will allow for more targeted and personalised approaches for prevention and management of CVD (94%). From the interviews (n = 15, 87% female, 43 ± 17 years, 87% dietitian), three themes were identified: (1) ‘On the periphery of care’—HCPs are aware of the role of genetics in health and are interested in knowing more, but it is not yet part of usual practice; (2) ‘A piece of the puzzle’—using genetic testing could be a tool to help personalise, prioritise and motivate participants; and (3) ‘Whose role is it?’—There is uncertainty regarding HCP roles and knowing exactly whose role it is to educate patients. Healthcare professionals are interested in using genetics to tailor dietary advice for CVD, but potential implications for patients need to be considered. Upskilling is required to increase their knowledge and confidence in this area. Further clarity regarding HCP roles in patient education is needed before this can be implemented in practice.

Heat-related mortality risks are a substantial component of the looming costs of climate change in the United States and globally. This article presents the results from a risk-risk survey to test whether U.S. respondents place a valuation premium on mortality risks from heat relative to cancer and transportation risks. The questionnaire exploits exogenous shocks to temperatures during a heat wave and randomized elements to further test whether preferences vary with heat exposure or the age of individuals exposed to heat risks. The results provide strong evidence that there is no valuation premium in the U.S. for heat-related risks. Subjects valued cancer risks twice as highly as heat and transportation risks, the latter of which are a common benchmark for general traumatic fatalities. While there is some evidence that subjects value heat risks more when exposed to a heat shock of approximately 3–4 °C, the size of the differential is too small to establish a statistically significant heat risk premium. Finally, subjects’ responses demonstrate no differential valuation of mortality risks to seniors versus the general population based on the preferences of the general population or the senior subsample.

Objectives/Goals: Manual skin assessment in chronic graft-versus-host disease (cGVHD) can be time consuming and inconsistent (>20% affected area) even for experts. Building on previous work we explore methods to use unmarked photos to train artificial intelligence (AI) models, aiming to improve performance by expanding and diversifying the training data without additional burden on experts. Methods/Study Population: Common to many medical imaging projects, we have a small number of expert-marked patient photos (N = 36, n = 360), and many unmarked photos (N = 337, n = 25,842). Dark skin (Fitzpatrick type 4+) is underrepresented in both sets; 11% of patients in the marked set and 9% in the unmarked set. In addition, a set of 20 expert-marked photos from 20 patients were withheld from training to assess model performance, with 20% dark skin type. Our gold standard markings were manual contours around affected skin by a trained expert. Three AI training methods were tested. Our established baseline uses only the small number of marked photos (supervised method). The semi-supervised method uses a mix of marked and unmarked photos with human feedback. The self-supervised method uses only unmarked photos without any human feedback. Results/Anticipated Results: We evaluated performance by comparing predicted skin areas with expert markings. The error was given by the absolute difference between the percentage areas marked by the AI model and expert, where lower is better. Across all test patients, the median error was 19% (interquartile range 6 – 34) for the supervised method and 10% (5 – 23) for the semi-supervised method, which incorporated unmarked photos from 83 patients. On dark skin types, the median error was 36% (18 – 62) for supervised and 28% (14 – 52) for semi-supervised, compared to a median error on light skin of 18% (5 – 26) for supervised and 7% (4 – 17) for semi-supervised. Self-supervised, using all 337 unmarked patients, is expected to further improve performance and consistency due to increased data diversity. Full results will be presented at the meeting. Discussion/Significance of Impact: By automating skin assessment for cGVHD, AI could improve accuracy and consistency compared to manual methods. If translated to clinical use, this would ease clinical burden and scale to large patient cohorts. Future work will focus on ensuring equitable performance across all skin types, providing fair and accurate assessments for every patient.

Objectives/Goals: The timing of neurosurgery is highly variable for post-hemorrhagic hydrocephalus (PHH) of prematurity. We sought to utilize microvascular imaging (MVI) in ultrasound (US) to identify biomarkers to discern the opportune time for intervention and to analyze the cerebrospinal fluid (CSF) characteristics as they pertain to neurosurgical outcome. Methods/Study Population: The inclusion criteria for the study are admission to the neonatal intensive care unit (NICU) with a diagnosis of Papile grade III or IV. Exclusion criteria are congenital hydrocephalus and hydrocephalus secondary to myelomeningocele/brain tumor/vascular malformation. We are a level IV tertiary referral center. Our current clinical care pathway utilizes brain US at admission and at weekly intervals. Patients who meet certain clinical and radiographic parameters undergo temporary or permanent CSF diversion. Results/Anticipated Results: NEL was implemented at our institution for PHH of prematurity in fall 2022. To date, we have had 20 patients who were diagnosed with grade III or IV IVH, of which 12 qualified for NEL. Our preliminary safety and feasibility results as well as the innovative bedside technique pioneered at our institution are currently in revision stages for publication. Preliminary results of the MVI data have yielded that hyperemia may confer venous congestion in the germinal matrix, which should then alert the neurosurgeon to delay any intervention to avoid progression of intraventricular blood. With regard to CSF characteristics, we anticipate that protein, cell count, hemoglobin, iron, and ferritin will decrease with NEL. Discussion/Significance of Impact: The timing of PHH of prematurity is highly variable. We expect that MVI will offer radiographic biomarkers to guide optimal timing of neurosurgical intervention. A better understanding of CSF characteristics could potentially educate the neurosurgeon with regard to optimal timing of permanent CSF diversion based on specific CSF parameters.

Objectives/Goals: Community members in North Central Florida who were identified with high mental health burden, through completion of a Health Needs Assessment in our community engagement program, experienced higher rates of health disparities like food insecurity, recent marijuana use, and burden of disease compared to persons with lower mental health burden. Methods/Study Population: Data were collected through HealthStreet, a University of Florida community engagement program to reduce disparities in healthcare and research. Multivariate and logistic regression analyses were conducted to identify differences between community members with high mental health burden (HMHB; reported depression and scored 8–10 on the stress/loneliness scale) and people with low mental health burden (LMHB; no reported depression and scored 1–7 on the stress/loneliness scale) on age, sex, race, food insecurity, trust in research/researchers, recent marijuana use, high blood pressure, and anxiety. Results/Anticipated Results: Among 3,736 CMs, 21.9% (n = 819) were considered to have high mental health burden. They were statistically significantly more likely to be middle-aged (37.9% vs. 31.2% LMHB), food insecure (62.6% vs. 35.2% LMHB), self-reported marijuana use in the past 30 days (29.2% vs. 15.5% LMHB), and experienced anxiety (70.8% vs. 34.4% LMHB). There were no differences by sex or trust. Discussion/Significance of Impact: People with HMHB do in fact have more disparities than people with LMHB but trust in research(ers) is not affected. These disparities contribute to significant distress over the lifespan. HealthStreet has engaged people with higher mental health burden and provided social referrals, which is crucial to reduce disparities and improve outcomes.

Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.

Greenwashing cases holding businesses to account for false or misleading eco-claims are an increasingly visible component of the business and human rights landscape globally. In the European Union (EU), the Unfair Commercial Practices Directive is the centrepiece of regulation for business-to-consumer claims. Within the European Green Deal initiative, the EU is revising this framework, first with the Directive to ‘Empower Consumers for the Green Transition,’ and second the pending proposal for a ‘Green Claims Directive,’ introducing detailed requirements on the substantiation and communication of ‘green claims’ to consumers. If fully adopted, this fundamental reform will impose greater restraints on the discretion of any authority charged with the assessment of green claims and provide more uniform criteria across the EU, resulting in more accurate environmental claims and greater clarity for consumers and businesses alike.

Paediatric ventricular assist device patients, including those with single ventricle anatomy, are increasingly managed outside of the ICU. We used retrospective chart review of our single centre experience to quantify adverse event rates and ICU readmissions for 22 complex paediatric patients on ventricular assist device support (15 two ventricles, 7 single ventricle) after floor transfer. The median age was 1.65 years. The majority utilised the Berlin EXCOR (17, 77.3%). There were 9 ICU readmissions with median length of stay of 2 days. Adverse events were noted in 9 patients (41%), with infection being most common (1.8 events per patient year). There were no deaths. Single ventricle patients had a higher proportion of ICU readmission and adverse events. ICU readmission rates were low, and adverse event rates were comparable to published rates suggesting ventricular assist device patients can be safely managed on the floor.

We provide an assessment of the Infinity Two fusion pilot plant (FPP) baseline plasma physics design. Infinity Two is a four-field period, aspect ratio $A = 10$, quasi-isodynamic stellarator with improved confinement appealing to a max-$J$ approach, elevated plasma density and high magnetic fields ($ \langle B\rangle = 9$ T). Here $J$ denotes the second adiabatic invariant. At the envisioned operating point ($800$ MW deuterium-tritium (DT) fusion), the configuration has robust magnetic surfaces based on magnetohydrodynamic (MHD) equilibrium calculations and is stable to both local and global MHD instabilities. The configuration has excellent confinement properties with small neoclassical transport and low bootstrap current ($|I_{bootstrap}| \sim 2$ kA). Calculations of collisional alpha-particle confinement in a DT FPP scenario show small energy losses to the first wall (${\lt}1.5 \,\%$) and stable energetic particle/Alfvén eigenmodes at high ion density. Low turbulent transport is produced using a combination of density profile control consistent with pellet fueling and reduced stiffness to turbulent transport via three-dimensional shaping. Transport simulations with the T3D-GX-SFINCS code suite with self-consistent turbulent and neoclassical transport predict that the DT fusion power$P_{{fus}}=800$ MW operating point is attainable with high fusion gain ($Q=40$) at volume-averaged electron densities $n_e\approx 2 \times 10^{20}$ m$^{-3}$, below the Sudo density limit. Additional transport calculations show that an ignited ($Q=\infty$) solution is available at slightly higher density ($2.2 \times 10^{20}$ m$^{-3}$) with $P_{{fus}}=1.5$ GW. The magnetic configuration is defined by a magnetic coil set with sufficient room for an island divertor, shielding and blanket solutions with tritium breeding ratios (TBR) above unity. An optimistic estimate for the gas-cooled solid breeder designed helium-cooled pebble bed is TBR $\sim 1.3$. Infinity Two satisfies the physics requirements of a stellarator fusion pilot plant.

In this work, we present a detailed assessment of fusion-born alpha-particle confinement, their wall loads, and stability of Alfvén eigenmodes driven by these energetic particles in the Infinity Two Fusion Pilot Plant Baseline Plasma Design, a 4-field-period quasiisodynamic stellarator to operate in deuterium-tritium fusion conditions. Using the Monte-Carlo codes SIMPLE, ASCOT5, and KORC-T, we study the collisionless and collisional dynamics of guiding-center and full-orbit alpha-particles in the core plasma. We find that core energy losses to the wall are less than 4%. Our simulations shows that peak power loads on the wall of this configuration are around 2.5 MW/m2 and are spatially localized, toroidally, and poloidaly in the vicinity of x-points of the magnetic island chain n/m = 4/5 outside the plasma volume. Also, an exploratory analysis using various simplified walls shows that shaping and distance of the wall from the plasma volume can help reduce peak power loads. Our stability assessment of Alfvén eigenmodes using the STELLGAP and FAR3d codes shows the absence of unstable modes driven by alpha-particles in Infinity Two due to the relatively low alpha-particle beta at the envisioned 800 MW operating scenario.