The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Product architecture decisions are made early in the product development process and have far-reaching effects. Unless anticipated through experience or intuition, many of these effects may not be apparent until much later in the development process, making changes to the architecture costly in time, effort, and resources. Many researchers through the years have studied various elements of product architecture and their effects. By aggregating observations on the effects of architecture strategies from a selection of the literature on the topic and storing them in a systematic data set, this information can be recalled in a matrix structure which allows for the identification, comparison and evaluation, and then selection of the most desirable product architecture strategies before expending resources along any development path. This paper introduces this matrix, referred to as the Product Architecture Strategy and Effect (PASE) Matrix, how to construct one, and a demonstration of its use.

The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing their surgical-site infection (SSI) prevention efforts. This document updates the Strategies to Prevent Surgical Site Infections in Acute Care Hospitals published in 2014.1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.

Drawing from two strands of ecological psychology, we suggest that even if social robots are interactive depictions, people need not mentally represent them as such. Rather, people can engage with the opportunities for action or affordances that social robots offer to them. These affordances are constrained by the larger sociocultural settings within which human–robot interactions occur.

Profitability, yield, and fertilizer use are compared across three different potassium (K) fertilizer rate recommendation ideologies. Existing agronomic, “build and maintain” rate recommendations (KE) are compared to profit-maximizing rates with and without taking long-run soil-test K (STK) implications into account. Regardless of starting STK, K use equilibrated over the course of 3 years irrespective of ideology. Since taking long-run STK into account did not alter ending STK and only led to a miniscule yield effect, we encourage producers to use annual profit-maximizing K rates that were 3–11% lower than KE rates and generated more profit with minimal yield loss.

While we applaud Bruineberg et al.'s analysis of the differences between Markov blankets and Friston blankets, we think it is not carried out to its ultimate consequences. There are reasons to think that, once Friston blankets are accepted as a theoretical construct, they do not do the work proponents of free energy principle (FEP) attribute to them. The emperor is indeed naked.

Yarkoni correctly recognizes that one reason for psychology's generalizability crisis is the failure to account for variance within experiments. We argue that this problem, and the generalizability crisis broadly, is a necessary consequence of the stimulus-response paradigm widely used in psychology research. We point to another methodology, perturbation experiments, as a remedy that is not vulnerable to the same problems.

The Variables and Slow Transients Survey (VAST) on the Australian Square Kilometre Array Pathfinder (ASKAP) is designed to detect highly variable and transient radio sources on timescales from 5 s to $\sim\!5$ yr. In this paper, we present the survey description, observation strategy and initial results from the VAST Phase I Pilot Survey. This pilot survey consists of $\sim\!162$ h of observations conducted at a central frequency of 888 MHz between 2019 August and 2020 August, with a typical rms sensitivity of $0.24\ \mathrm{mJy\ beam}^{-1}$ and angular resolution of $12-20$ arcseconds. There are 113 fields, each of which was observed for 12 min integration time, with between 5 and 13 repeats, with cadences between 1 day and 8 months. The total area of the pilot survey footprint is 5 131 square degrees, covering six distinct regions of the sky. An initial search of two of these regions, totalling 1 646 square degrees, revealed 28 highly variable and/or transient sources. Seven of these are known pulsars, including the millisecond pulsar J2039–5617. Another seven are stars, four of which have no previously reported radio detection (SCR J0533–4257, LEHPM 2-783, UCAC3 89–412162 and 2MASS J22414436–6119311). Of the remaining 14 sources, two are active galactic nuclei, six are associated with galaxies and the other six have no multi-wavelength counterparts and are yet to be identified.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

ABSTRACT IMPACT: Interdisciplinary networks represent critical components of translational science and learning system development. Our work impacts translational research by presenting an evidence-based approach to developing interdisciplinary networks in response to the COVID-19 pandemic; the approach presented may have broad applications within other academic institutions and medical centers. OBJECTIVES/GOALS: As a local response to the COVID-19 pandemic, we established the University of Alabama at Birmingham COVID-19 Collaborative Outcomes Research Enterprise (CORE) as an interdisciplinary learning health system (LHS) to achieve an integrated health services and outcomes research response amid the pandemic. METHODS/STUDY POPULATION: We adapted a learning system framework, based upon a scoping review of the literature and the Knowledge to Action Framework for implementation science. Leveraging this framework, we developed an institutional-level collaborative network of extant expertise and resources to rapidly develop an interdisciplinary response to COVID-19. The network was designed to quickly collect newly published or clinical information related to COVID-19, to evaluate potential usefulness of this information, and to disseminate the new knowledge throughout the interdisciplinary network; we strove to engage a wide variety of expertise and skills in the network. Thus, we subsequently used social network analysis to examine the emergence of informal work patterns and diversified network capabilities based on the LHS framework. RESULTS/ANTICIPATED RESULTS: We identified three principal characteristics of institutional LHS development including: 1.) identifying network components; 2.) building the institutional collaborative network; and 3.) diversifying network capabilities. Seven critical components of LHS were identified including: 1.) collaborative and executive leadership, 2.) research coordinating committee, 3.) oversight and ethics committee, 4.) thematic scientific working groups, 5.) programmatic working groups, 6.) informatics capabilities, and 7.) patient advisory groups. Evolving from the topical interests of the initial CORE participants, three scientific working groups (health disparities, neurocognition, and critical care) were developed to support the learning network. DISCUSSION/SIGNIFICANCE OF FINDINGS: Interdisciplinary collaborative networks are critical to the development of LHS. The COVID-19 CORE LHS framework served as a foundational resource that may support further institutional-level efforts to develop responsive learning networks. The LHS approach presented may have broad applications within other academic institutions and centers.

To understand hospital policies and practices as the COVID-19 pandemic accelerated, the Society for Healthcare Epidemiology of America (SHEA) conducted a survey through the SHEA Research Network (SRN). The survey assessed policies and practices around the optimization of personal protection equipment (PPE), testing, healthcare personnel policies, visitors of COVID-19 patients in relation to procedures, and types of patients. Overall, 69 individual healthcare facilities responded in the United States and internationally, for a 73% response rate.

We agree with Heyes that an explanation of human uniqueness must appeal to cultural evolution, and not just genes. Her account, though, focuses narrowly on internal cognitive mechanisms. This causes her to mischaracterize human behavior and to overlook the role of material culture. A more powerful account would view cognitive gadgets as spanning organisms and their (shared) environments.

OBJECTIVES/SPECIFIC AIMS: The purpose of the present secondary data analysis was to examine the effect of moderate-severe disturbed sleep before the start of radiation therapy (RT) on subsequent RT-induced pain. METHODS/STUDY POPULATION: Analyses were performed on 676 RT-naïve breast cancer patients (mean age 58, 100% female) scheduled to receive RT from a previously completed nationwide, multicenter, phase II randomized controlled trial examining the efficacy of oral curcumin on radiation dermatitis severity. The trial was conducted at 21 community oncology practices throughout the US affiliated with the University of Rochester Cancer Center NCI’s Community Oncology Research Program (URCC NCORP) Research Base. Sleep disturbance was assessed using a single item question from the modified MD Anderson Symptom Inventory (SI) on a 0–10 scale, with higher scores indicating greater sleep disturbance. Total subjective pain as well as the subdomains of pain (sensory, affective, and perceived) were assessed by the short-form McGill Pain Questionnaire. Pain at treatment site (pain-Tx) was also assessed using a single item question from the SI. These assessments were included for pre-RT (baseline) and post-RT. For the present analyses, patients were dichotomized into 2 groups: those who had moderate-severe disturbed sleep at baseline (score≥4 on the SI; n=101) Versus those who had mild or no disturbed sleep (control group; score=0–3 on the SI; n=575). RESULTS/ANTICIPATED RESULTS: Prior to the start of RT, breast cancer patients with moderate-severe disturbed sleep at baseline were younger, less likely to have had lumpectomy or partial mastectomy while more likely to have had total mastectomy and chemotherapy, more likely to be on sleep, anti-anxiety/depression, and prescription pain medications, and more likely to suffer from depression or anxiety disorder than the control group (all p’s≤0.02). Spearman rank correlations showed that changes in sleep disturbance from baseline to post-RT were significantly correlated with concurrent changes in total pain (r=0.38; p<0.001), sensory pain (r=0.35; p<0.001), affective pain (r=0.21; p<0.001), perceived pain intensity (r=0.37; p<0.001), and pain-Tx (r=0.35; p<0.001). In total, 92% of patients with moderate-severe disturbed sleep at baseline reported post-RT total pain compared with 79% of patients in the control group (p=0.006). Generalized linear estimating equations, after controlling for baseline pain and other covariates (baseline fatigue and distress, age, sleep medications, anti-anxiety/depression medications, prescription pain medications, and depression or anxiety disorder), showed that patients with moderate-severe disturbed sleep at baseline had significantly higher mean values of post-RT total pain (by 39%; p=0.033), post-RT sensory pain (by 41%; p=0.046), and post-RT affective pain (by 55%; p=0.035) than the control group. Perceived pain intensity (p=0.066) and pain-Tx (p=0.086) at post-RT were not significantly different between the 2 groups. DISCUSSION/SIGNIFICANCE OF IMPACT: These findings suggest that moderate-severe disturbed sleep prior to RT is an important predictor for worsening of pain at post-RT in breast cancer patients. There could be several plausible reasons for this. Sleep disturbance, such as sleep loss and sleep continuity disturbance, could result in impaired sleep related recovery and repair of tissue damage associated with cancer and its treatment; thus, resulting in the amplification of pain. Sleep disturbance may also reduce pain tolerance threshold through increased sensitization of the central nervous system. In addition, pain and sleep disturbance may share common neuroimmunological pathways. Sleep disturbance may modulate inflammation, which in turn may contribute to increased pain. Further research is needed to confirm these findings and whether interventions targeting sleep disturbance in early phase could be potential alternate approaches to reduce pain after RT.