We investigate the influence of insoluble surfactants on the spatio-temporal evolution of breaking waves, focusing on both regular and spilling regimes. Three-dimensional direct numerical simulations are conducted using an interface-tracking/level-set method that incorporates surfactant-induced Marangoni stresses. The simulations reveal that surfactant gradients, through Marangoni stresses, markedly alter the wave dynamics. While regular breakers exhibit only minor modifications in the presence of surfactants, increasing surfactant-induced Marangoni stresses in spilling breakers leads to changes in the crest evolution and vorticity generation. Surfactants enhance spilling breakers, primarily driven by Marangoni stresses rather than surface tension reduction. To quantify these effects, we also extend circulation-based theoretical frameworks to account for surfactant contributions.

Recent developments in widefield radio telescopes have enabled searches of a new region of parameter space in the time domain: timescales of seconds to minutes, that have been overlooked in traditional surveys. These searches have revealed a new population of sources: long period transients, which typically show periodic behaviour of minutes to hours. In addition they have detected phenomena ranging from extreme scintillation to stellar radio bursts. However, almost all searches to date have involved archival data that has been processed in offline, batch mode. In this context, we present VASTER, the first short-timescale imaging and transient detection pipeline running in real time on a widefield radio telescope. VASTER has been running on the Australian SKA Pathfinder (ASKAP) since July 2025, and images most of the ASKAP survey project data on timescales of 15 minutes. In this paper we describe the VASTER system, and present the results from the first two weeks of operation, including the discovery of two long period transients: ASKAP J165130.3–450520 with a period of 6.48 hours and ASKAP J170036.6–445758 with a period of 4.69 hours. The detection of these two sources adds to the small, but growing, population of long period transients, as well as demonstrating the potential of VASTER to explore this region of transient parameter space.

Drylands cover 41% of Earth’s land surface, support 36% of the global population and contribute 60% of global food production. Despite these ecosystems’ importance and high vulnerability to droughts and heatwaves, drylands remain some of the most understudied systems on Earth. Monitoring drylands is challenging due to their complex ecosystem structure of visible soil mixed with diverse plant species that respond rapidly to weather and climate. In 2023 and 2024, a NASA scoping study was conducted for a proposed dryland terrestrial ecology field campaign called Adaptation and Response in Drylands (ARID). Thereafter, the NASA ARID scoping team submitted their campaign proposal to NASA Headquarters, providing a study design for how field, aircraft and satellite measurements, as well as modeling, could address the most critical fundamental and applied science questions in drylands. The extensive strategic vision was created by and for the drylands research community, including remote sensors, modelers, experimentalists and ecologists from across the world, and the overall approach can be further utilized and altered for different uses and data information needs. Here, we summarize the final ARID research agenda, including its main objectives, field campaign strategy, data end-user support strategy, and U.S. and global community engagement.

Objectives/Goals: Safely and effectively translating AI classification models requires robust post-deployment monitoring. Yet there is little guidance about how to do so. Here, we outline how standard machine learning model development study designs are insufficient for post-deployment monitoring, and what specific study designs are needed. Methods/Study Population: We made original linkages between machine learning methodology and biostatistics, particularly to diagnostic testing, for study design guidance on post-deployment model performance and fairness assessment. Results/Anticipated Results: The kind of case–control sampling typically used for model development cannot give valid estimates of the Positive Predictive Value (precision) and may suffer from verification bias; in a pragmatic clinical trial, or under deployment, only the PPV can be measured, unless there is random confirmatory testing of predicted negatives. This is important for measuring sensitivity, specificity, and False Omission Rate as a fairness metric. Discussion/Significance of Impact: By linking well-understood biostatistics principles (e.g., diagnostic testing) to machine learning classifier evaluation, we show what is required for rigorous evaluation of models in clinical practice. This will establish clear guidance and rigorous standards of practice for study design and analytic aspects of post-deployment monitoring.

Objectives/Goals: This scoping review aims to synthesize current literature on post-deployment monitoring of AI-enabled digital health solutions within clinical practice. Findings identify existing approaches and gaps that inform guidance for post-deployment monitoring in clinical practice. Methods/Study Population: We conducted a scoping review in accordance with PRISMA-ScR guidelines to characterize the current landscape of post-deployment monitoring in healthcare systems. A PubMed search targeted peer-reviewed articles in English published between 2015 and mid-2025, including text or MeSH terms on 1) health system/hospital; 2) artificial intelligence; 3) post-deployment; and 4) evaluation/monitoring. We performed a thematic analysis to identify common challenges, gaps, and opportunities in AI oversight. Additionally, we reviewed guidelines addressing post-deployment AI monitoring. All analyses were conducted using Rayyan.ai and Microsoft Word. Results/Anticipated Results: Among the six studies included after the full-text review, five provide recommendations to ensure transparency, safety, and model performance. These recommendations encompassed monitoring model performance and real-time case report, post-market surveillance, adverse event reporting, end-user training, data standardization and documentation, and interdisciplinary collaboration. One study reports a framework for post-deployment impact grading. Currently, no guidelines addressing post-deployment of AI monitoring in health systems exist. Our findings highlight the urgent need for structured post-deployment processes to ensure AI in healthcare systems is safe, effective, and trustworthy. Discussion/Significance of Impact: The absence of post-deployment guidelines raises concerns. This review underscores the need for interdisciplinary collaboration to establish a post-deployment monitoring process with scientific rigor, scalability, and sustainability that aligns with operational realities.

Objectives/Goals: Ovarian cancer is the most lethal gynecologic cancer with emergence of recurrent and resistant disease being frequent. We sought to identify novel ways to effectively kill chemotherapy-resistant forms of ovarian cancer and to prevent recurrence following curative intent with surgical and adjuvant regimens. Methods/Study Population: Our group identified CTPS1 as a novel dependency in triple negative breast cancer (TNBC) and ovarian cancer. We found CTPS1 was highly expressed in breast and ovarian tumor tissues and therapy-resistant models. We demonstrated siRNA knockdown of CTPS1 reduced proliferation in sensitive and resistant cell lines. In collaboration with Step Pharma, who developed the first CTPS1 inhibitor (STP938), we performed genome-wide CRISPR KO screens on STP938-sensitive and -resistant cells. Top synthetic lethal hits identified included TSC1, TSC2, and PPP2R2A. Synergy assays were conducted with STP938 in combination with mTOR inhibitors (Everolimus, Sirolimus, and Temsirolimus) and the PPP2R2A inhibitor LB-100 to evaluate the therapeutic benefit of combination therapies. Results/Anticipated Results: We identified CTPS1 as a novel vulnerability in many ovarian cancer cell line models, including models of chemotherapy and/or PARP inhibitor resistance. The first-in-class CTPS1 inhibitor (STP938) was shown to be a highly effective anticancer agent in sensitive and resistant forms of ovarian cancer, both in vitro and in vivo. Genome-wide CRISPR KO screens identified central components of the mTOR pathway (TSC1 and TSC2), as well as PPP2R2A, as synthetic lethal targets in the setting of STP938 exposure. We anticipate that combinatorial treatment of mTOR inhibitors and PP2R2A inhibitors with STP938 will further enhance efficacy and reduce the risk of recurrence when used in the adjuvant treatment of ovarian cancer patients. Discussion/Significance of Impact: This study will validate synthetic lethal interactions from our CRISPR screen, reveal genes that could be mutated in ovarian cancer patients that may be driving resistance to STP938, and uncover combination therapies that can be used to increase efficacy in ovarian cancer patients treated with STP938.

Objectives/Goals: Trial accrual via electronic health records (EHRs) are limited by workflow and communication issues. We used a root cause analysis to identify barriers and guide changes in a pragmatic trial of metformin vs lifestyle change for prostate cancer. The goal is to evaluate strategies to increase accrual. Methods/Study Population: We previously conducted a mixed-methods root cause analysis to examine barriers along the enrollment pathway. The study required two consents: 1) prostate cancer research consortium participation and 2) trial specific. We assessed the trial’s EHR-embedded consent workflow and Best Practice Alert (BPA) implementation and aggregated and harmonized data from multiple EHR sources to reconstruct the full enrollment pathway in a CONSORT diagram. We conducted semi-structured interviews with eligible patients (n = 10) and engaged clinicians (n = 4). Based on interview findings and enrollment pathway insights, the study team designed and evaluated impact of several accrual enhancement strategies. Results/Anticipated Results: We identified two types of feasible accrual enhancement strategies: 1) patient-focused, including a) tracking consent status in the enrollment pathway report; b) proactively messaging patients with upcoming visits about consent; and 2) clinician-focused, including a) tailored EHR-based messages before eligible patient visits; b) targeted education; and c) BPA optimization to improve reach to appropriate clinicians. In the 6 months prior to strategy implementation, enrollment averaged 0.33 patients/month. In the 6 months post-implementation, enrollment increased to an average of 3.17 patients/month. Discussion/Significance of Impact: Sustained enrollment in pragmatic trials demands greater-than-expected engagement. In partnership, the study and informatics teams oversaw intervention processes based on trial-specific issues, identified issues quickly, explored feasible solutions, and refined the process to support trial success.

Spectral-line results from a new cryogenic phased array feed (cryoPAF) on the Murriyang telescope at Parkes are presented. This array offers a significant improvement in field of view, aperture efficiency, bandwidth, chromaticity, and survey speed compared with conventional horn-fed receivers. We demonstrate this with measurements of sky calibrators and observations of 21-cm neutral hydrogen (HI) in the Large Magellanic Cloud (LMC) and the nearby galaxy NGC 6744. Within 0.3 deg of the optical axis, the ratio of system temperature to dish aperture efficiency ($T_\mathrm{sys}/\eta_{d}$) is 25 K, and the ratio with beam efficiency ($T_\mathrm{sys}/\eta_\mathrm{mb}$) is 21 K (at 1.4 GHz). For the previously measured $T_\mathrm{sys} = 17$ K, respective efficiency values $\eta_{d} \approx 0.7$ and $\eta_\mathrm{mb} \approx 0.8$ are derived. Our HI observational results are in good agreement with previous results, although detailed comparison with multibeam observations of the LMC suggests that the earlier observations may have missed an extended component of low-column-density gas ($\sim$$8\times 10^{18}$ cm$^{-2}$). We use the cryoPAF zoom-band and wideband data to make a preliminary investigation of whether the large number of simultaneous beams (72) permits the use of novel data reduction methods to reduce the effects of foreground/background continuum contamination and radio-frequency interference (RFI). We also investigate if these methods can better protect against signal loss for the detection of faint, extended cosmological signals such as HI intensity maps. Using robust higher-order singular value decomposition (SVD) techniques, we find encouraging results for the detection of both compact and extended sources, including challenging conditions with high RFI occupancy and significant sky continuum structure. Examples are shown that demonstrate that 3D SVD techniques offer a significant improvement in noise reduction and signal capture compared with more traditional layered 2D techniques.

Entropically driven fluid–solid transitions in monodisperse, purely repulsive hard spheres (MPRHS) are well established in theory, simulation and experiment for atomic and colloidal systems. For MPRHS, however, coexistence is usually located via bulk free-energy calculations; the underlying microscopic balance between configurational and vibrational entropy is left implicit. Frenkel clarified this mechanism explicitly as an exchange of long-range configurational entropy for short-range vibrational entropy, but in the pristine MPRHS limit the nucleation barrier near coexistence is so high that phase separation is predicted only on astronomical time scales. Consistent with this, even unbiased simulations do not show spontaneous, equilibrium fluid–crystal coexistence; transient mixtures are mostly overtaken by a single phase; observed coexistence is still algorithmically driven. Nearly hard-sphere colloid experiments do observe fluid–crystal coexistence, but always in the presence of unavoidable triggers such as gravity and walls. We treat the hard-sphere phase diagram as settled and ask how the entropic exchange mechanism can be revealed in nearly hard-sphere colloidal simulations. We probe the mechanism on finite time scales by introducing minimal perturbations that trigger phase separation: small reductions in hardness that increase locally accessible free volume (and thus gently increase vibrational entropy), and 2 %–4 % distributed crystal seeds. These perturbations produce coexisting fluid and crystal domains with crystal fraction, phase envelope and osmotic pressure that, with systematically increasing particle hardness, approach the hard-sphere limit. These results demonstrate that slight enhancements to vibrational entropy provide a dynamically accessible route to realising the long-range/short-range entropy exchange required for phase separation.

Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot], a cool-season forage crop in temperate countries, is also a major weed problem in winter crops, especially wheat (Triticum aestivum L.). Understanding the molecular mechanisms underlying its adaptive traits is crucial for managing L. perenne ssp. multiflorum as both a crop and a weed species. Genome-wide association studies (GWAS) were performed using single-nucleotide polymorphism (SNP) data from double-digest restriction site–associated DNA (ddRADseq) sequencing to assess the genetic diversity and identify the genetic region(s) associated with key adaptive traits, namely tillering ability, regrowth rate, and seed shattering in this species. A collection of 56 wild/weedy populations, 25 half-sib breeding lines, four commercial cultivars, and one reference sample each of L. perenne ssp. multiflorum, perennial ryegrass (Lolium perenne L.), rigid ryegrass (Lolium rigidum Gaudin), and poison ryegrass (Lolium temulentum L.) obtained from the USDA-GRIN were used for the study. About 3,079 SNPs were used for principal component and marker–trait association analyses. In the principal component analysis, the half-sibs, cultivars, and wild populations clustered separately; however, a few wild populations were mixed with the half-sibs. Sequence annotation of the flanking sequences of significant SNPs identified in GWAS with the NCBI database revealed potential candidate genes underlying the traits, including Ethylene receptor2 promoting regrowth in common barley (Hordeum vulgare L.) and other species; an auxin-responsive protein SAUR36-like controlling tiller production in Tausch’s goatgrass (Aegilops tauschii Coss.) and rivet wheat (https://plants.sc.egov.usda.gov/plant-profile/AETA2) (Triticum turgidum L.; syn.: Triticum dicoccoides Koern. ex Schweinf.); and 4-coumarate-coenzyme A ligase for reduced seed shattering in L. perenne and L. rigidum. This information on marker–trait associations for these traits in L. perenne ssp. multiflorum will aid in manipulating the traits in crop breeding and weed management programs.

To reveal the influence laws of casing abradable coating wear on compressor aerodynamic performance, a numerical simulation study was conducted on the performance of Rotor 37 under high-speed scraping conditions with different hardness coating wear morphologies. The results show that compressor isentropic efficiency and outlet mass flow are sensitive to scraping-induced morphology changes. The medium-hardness coating causes the most significant performance degradation, with maximum reductions reaching 1.96% and 1.39%, respectively, while the pressure ratio shows little variation. Scraping grooves aggravate mixing losses between leading-edge (LE) leakage flow and mid-chord (MID) leakage flow. The tip leakage flow pushes suction-side separation vortices toward the main flow path. Under medium-hardness coating scraping conditions, the maximum entropy generation region affects up to 9.1% blade height and induces tip leakage vortex-shockwave interactions, resulting in substantial tip losses. The compressor aerodynamic performance is less affected by wear zone roughness, with the maximum isentropic efficiency reduction being only 0.31%. When wear zone roughness increases, near-wall turbulence fluctuations intensify and separation zones expand, causing flow structure changes in tip leakage paths and blade wake regions, which shifts the compressor aerodynamic characteristics toward lower flow rates. The study demonstrates that coating hardness alters leakage flow structures through wear morphology depth: medium-hardness coatings with the deepest wear grooves exhibit maximum performance deterioration, while high-hardness coatings show better wear resistance and performance maintenance.