Herbicide-resistant Palmer amaranth is creating additional challenges for producers choosing to adopt a furrow-irrigated rice production system due to the absence of a sustained flood, enabling extended weed emergence. Fluridone has been shown to control Palmer amaranth effectively in cotton production systems and was recently registered for use in rice. Experiments were initiated in 2022 and 2023 to evaluate 1) Palmer amaranth control and rice tolerance to preemergence- and postemergence-applied fluridone at a 0.5x (84 g ai ha-1) and 1x rate (168 g ai ha-1) on a silt loam soil and 2) the effect of various herbicide programs containing fluridone on Palmer amaranth biomass, seed production, and rough rice grain yield. Preemergence applications of fluridone at a 1x rate in combination with clomazone resulted in 84% control of Palmer amaranth 21 d after treatment (DAT). Fluridone, in combination with clomazone preemergence, caused up to 36% rice injury 21 DAT; however, early season injury did not negatively affect rice yields. Palmer amaranth biomass and fecundity were reduced with herbicide programs that included fluridone plus florpyrauxifen-benzyl, and, in some instances, there was no Palmer amaranth biomass or seed production following multiple applications of both herbicides. Fluridone- and florpyrauxifen-benzyl-based herbicide programs achieved effective control of Palmer amaranth when applied timely, but injury to hybrid rice is enhanced with preemergence applications of fluridone that are not permitted with the current label.

Translational research needs to show value through impact on measures that matter to the public, including health and societal benefits. To this end, the Translational Science Benefits Model (TSBM) identified four categories of impact: Clinical, Community, Economic, and Policy. However, TSBM offers limited guidance on how these areas of impact relate to equity. Central to the structure of our Center for American Indian and Alaska Native Diabetes Translation Research are seven regional, independent Satellite Centers dedicated to community-engaged research. Drawing on our collective experience, we provide empirical evidence about how TSBM applies to equity-focused research that centers community partnerships and recognizes Indigenous knowledge. For this special issue – “Advancing Understanding and Use of Impact Measures in Implementation Science” – our objective is to describe and critically evaluate gaps in the fit of TSBM as an evaluation approach with sensitivity to health equity issues. Accordingly, we suggest refinements to the original TSBM Logic model to add: 1) community representation as an indicator of providing community partners “a seat at the table” across the research life cycle to generate solutions (innovations) that influence equity and to prioritize what to evaluate, and 2) assessments of the representativeness of the measured outcomes and benefits.

The swelling of n-butylammonium vermiculite in water was investigated as a function of the sol concentration (r), the salt concentration (c) and the temperature (T).

The interlayer spacing in the gel phase was investigated as a function of r and c by neutron diffraction and by laboratory experiments which measured how many times its own volume a crystal would absorb. The salt concentration was found to be the stronger variable with the interlayer spacing decreasing proportional to c0.5, which is consistent with previous results and with the Coulombic attraction theory. The sol concentration was found to affect the swelling for two reasons, the salt fractionation effect and the trapped salt effect. Both of these cause the salt concentration in the supernatant fluid to be greater than that originally added to the crystals and so reduce the swelling.

A new method was used for extracting the solution from inside the gels by collapsing the gels by the addition of potassium hydrogen carbonate. The Volhardt titration was carried out on the extracted and supernatant solutions from about 250 gels. The ratio of the external to the internal chloride concentration was found to be approximately constant across the range of salt concentrations. Its average value was equal to 2.6, again in agreement with Coulombic attraction theory and showing the surface potential to be constant at about 70 mV.

The (r, c, T) boundary of the two phase colloid region was investigated by three methods. A plot of log c against Tc was linear within experimental accuracy, with a gradient of 0.077 K−1 or 13 K per log unit. This shows that the surface potential varies by only 1 mV per decade in the salt concentration. The system is therefore governed by the Dirichlet boundary condition and not by the Nernst equation.

For turbulent bubbly flows, multi-phase simulations resolving both the liquid and bubbles are prohibitively expensive in the context of different natural phenomena. One example is breaking waves, where bubbles strongly influence wave impact loads, acoustic emissions and atmospheric-ocean transfer, but detailed simulations in all but the simplest settings are infeasible. An alternative approach is to resolve only large scales, and model small-scale bubbles adopting sub-resolution closures. Here, we introduce a large eddy simulation smoothed particle hydrodynamics (SPH) scheme for simulations of bubbly flows. The continuous liquid phase is resolved with a semi-implicit isothermally compressible SPH framework. This is coupled with a discrete Lagrangian bubble model. Bubbles and liquid interact via exchanges of volume and momentum, through turbulent closures, bubble breakup and entrainment, and free-surface interaction models. By representing bubbles as individual particles, they can be tracked over their lifetimes, allowing closure models for sub-resolution fluctuations, bubble deformation, breakup and free-surface interaction in integral form, accounting for the finite time scales over which these events occur. We investigate two flows: bubble plumes and breaking waves, and find close quantitative agreement with published experimental and numerical data. In particular, for plunging breaking waves, our framework accurately predicts the Hinze scale, bubble size distribution, and growth rate of the entrained bubble population. This is the first coupling of an SPH framework with a discrete bubble model, with potential for cost-effective simulations of wave–structure interactions and more accurate predictions of wave impact loads.

Although the impacts of intensive agriculture on biodiversity and strategies for mitigating these effects have been widely described, small-scale, diversified farms and the opportunities they present for bird conservation have been less thoroughly examined. This omission is potentially significant, because this form of agriculture represents a growing sector of the industry in the populous northeastern USA, and the diverse habitats on these farms contrast with larger, structurally homogeneous intensive agriculture. To evaluate bird-habitat associations and conservation opportunities for supporting species of conservation concern on these small, diversified farms, we conducted avian point count and vegetation surveys across 23 farms in western Massachusetts during the summers of 2017 and 2018. We used Poisson-binomial mixture models and canonical correspondence analysis to assess the effects of a suite of microhabitat-, field- and landscape-scale (1 km buffer around the field) variables on the abundance of bird species. Our results confirmed that shrubland birds, a group of species of elevated conservation concern, accounted for 52% of the total observations, including song sparrow (Melospiza melodia), gray catbird (Dumatella carolinensis), common yellowthroat (Geothlypis trichas) and American goldfinch (Spinus tristis). Species–habitat relationships were diverse; however, smaller field sizes, and increased cover of tall, dense, woody or non-productive vegetation types were associated with higher abundance of shrubland species as well as lower abundance of crop pests such as European starling (Sturnus vulgaris) and house sparrow (Passer domesticus). These findings support the hypothesis that small, diversified farms are supporting birds of high conservation concern, and we provide species-specific guidelines for farmers interested in conserving birds on their land.

Knowledge of frontal ablation from marine-terminating glaciers (i.e., mass lost at the calving face) is critical for constraining glacier mass balance, improving projections of mass change, and identifying the processes that govern frontal mass loss. Here, we discuss the challenges involved in computing frontal ablation and the unique issues pertaining to both glaciers and ice sheets. Frontal ablation estimates require numerous datasets, including glacier terminus area change, thickness, surface velocity, density, and climatic mass balance. Observations and models of these variables have improved over the past decade, but significant gaps and regional discrepancies remain, and better quantification of temporal variability in frontal ablation is needed. Despite major advances in satellite-derived large-scale datasets, large uncertainties remain with respect to ice thickness, depth-averaged velocities, and the bulk density of glacier ice close to calving termini or grounding lines. We suggest ways in which we can move toward globally complete frontal ablation estimates, highlighting areas where we need improved datasets and increased collaboration.

The dynamics of interfaces in slow diffusion equations with strong absorption are studied. Asymptotic methods are used to give descriptions of the behaviour local to a comprehensive range of possible singular events that can occur in any evolution. These events are: when an interface changes its direction of propagation (reversing and anti-reversing), when an interface detaches from an absorbing obstacle (detaching), when two interfaces are formed by film rupture (touchdown) and when the solution undergoes extinction. Our account of extinction and self-similar reversing and anti-reversing is built upon previous work; results on non-self-similar reversing and anti-reversing and on the various types of detachment and touchdown are developed from scratch. In all cases, verification of the asymptotic results against numerical solutions to the full PDE is provided. Self-similar solutions, both of the full equation and of its asymptotic limits, play a central role in the analysis.

Despite becoming increasingly represented in academic departments, women scholars face a critical lack of support as they navigate demands pertaining to pregnancy, motherhood, and child caregiving. In addition, cultural norms surrounding how faculty and academic leaders discuss and talk about tenure, promotion, and career success have created pressure for women who wish to grow their family and care for their children, leading to questions about whether it is possible for these women to have a family and an academic career. This paper is a call to action for academia to build structures that support professors who are women as they navigate the complexities of pregnancy, the postpartum period, and the caregiving demands of their children. We specifically call on those of us in I-O psychology, management, and related departments to lead the way. In making this call, we first present the realistic, moral, and financial cases for why this issue needs to be at the forefront of discussions surrounding success in the academy. We then discuss how, in the U.S. and elsewhere, an absence of policies supporting women places two groups of academics—department heads (as the leaders of departments who have discretion outside of formal policies to make work better for women) and other faculty members (as potential allies both in the department and within our professional organizations)—in a critical position to enact support and change. We conclude with our boldest call—to make a cultural shift that shatters the assumption that having a family is not compatible with academic success. Combined, we seek to launch a discussion that leads directly to necessary and overdue changes in how women scholars are supported in academia.

OBJECTIVES/GOALS: The trabecular meshwork (TM) and Schlemm’s canal (SC), located within the iridocorneal angle (ICA), form the main outflow pathway and a major target for glaucoma treatments. We characterized the human ICA in vivo with Optical Coherence Tomography (OCT) imaging using a customized goniolens and a commercial OCT device (Heidelberg Spectralis). METHODS/STUDY POPULATION: Imaging these structures is difficult due to the optical limitations of imaging through the cornea at high angles. Therefore, a clinical gonioscopy lens was modified with a 12mm plano-convex lens placed on its anterior surface to focus light on the ICA structures, and capture returning light. Each subjects’ eye was anesthetized with 1 drop of Proparacaine 0.5%. The goniolens was coupled to the eye with gonio-gel and it was held by a 3D adjustable mount. OCT volume scans were acquired on 10 healthy subjects. The linear polarization of the OCT was rotated with a half-waveplate to measure dependence of the ICA landmarks on polarization orientation. RESULTS/ANTICIPATED RESULTS: The TM was seen in 9 of 10 subjects. Polarization rotation modified the brightness of the band of extracanalicular limbal lamina (BELL) and corneoscleral bands due to the birefringent nature of the collagenous structures, increasing the contrast of SC. SC width was 99 ± 20µm varying in size over space, including a subject with SC narrowing in the inferior-temporal quadrant. DISCUSSION/SIGNIFICANCE: This clinically suitable gonioscopic OCT approach has successfully been used to image the human ICA in 3D in vivo, providing detailed characterization of the TM and SC as well as enhancing their contrast against their birefringent backgrounds by rotating the polarization of the imaging beam.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.