With wide-field phased array feed technology, the Australian Square Kilometre Array Pathfinder (ASKAP) is ideally suited to search for seemingly rare radio transient sources that are difficult to discover previous-generation narrow-field telescopes. The Commensal Real-time ASKAP Fast Transient (CRAFT) Survey Science Project has developed instrumentation to continuously search for fast radio transients (duration ≲ 1 second) with ASKAP, with a particular focus on finding and localising Fast Radio Bursts (FRBs). Since 2018, the CRAFT survey has been searching for FRBs and other fast transients by incoherently adding the intensities received by individual ASKAP antennas, and then correcting for the impact of frequency dispersion on these short-duration signals in the resultant incoherent sum (ICS) in real-time. This low-latency detection enables the triggering of voltage buffers, which facilitates the localisation of the transient source and the study of spectro-polarimetric properties at high time resolution. Here we report the sample of 43 FRBs discovered in this CRAFT/ICS survey to date. This includes 22 FRBs that had not previously been reported: 16 FRBs localised by ASKAP to. ≲ 1 arcsec and 6 FRBs localised to ∼ 10 arcmin. Of the new arcsecond-localised FRBs, we have identified and characterised host galaxies (and measured redshifts) for 11. The median of all 30 measured host redshifts from the survey to date is z = 0.23. We summarise results from the searches, in particular those contributing to our understanding of the burst progenitors and emission mechanisms, and on the use of bursts as probes of intervening media. We conclude by foreshadowing future FRB surveys with ASKAP using a coherent detection system that is currently being commissioned. This will increase the burst detection rate by a factor of approximately ten and also the distance to which ASKAP can localise FRBs.

In this paper, we present and evaluate a novel Bayesian regime-switching zero-inflated multilevel Poisson (RS-ZIMLP) regression model for forecasting alcohol use dynamics. The model partitions individuals’ data into two phases, known as regimes, with: (1) a zero-inflation regime that is used to accommodate high instances of zeros (non-drinking) and (2) a multilevel Poisson regression regime in which variations in individuals’ log-transformed average rates of alcohol use are captured by means of an autoregressive process with exogenous predictors and a person-specific intercept. The times at which individuals are in each regime are unknown, but may be estimated from the data. We assume that the regime indicator follows a first-order Markov process as related to exogenous predictors of interest. The forecast performance of the proposed model was evaluated using a Monte Carlo simulation study and further demonstrated using substance use and spatial covariate data from the Colorado Online Twin Study (CoTwins). Results showed that the proposed model yielded better forecast performance compared to a baseline model which predicted all cases as non-drinking and a reduced ZIMLP model without the RS structure, as indicated by higher AUC (the area under the receiver operating characteristic (ROC) curve) scores, and lower mean absolute errors (MAEs) and root-mean-square errors (RMSEs). The improvements in forecast performance were even more pronounced when we limited the comparisons to participants who showed at least one instance of transition to drinking.

Yellow and knotroot foxtail are two common weed species infesting turfgrass and pastures in the southeastern region of the United States. Yellow and knotroot foxtail share morphological similarities and are frequently misidentified by weed managers, thus leading to confusion in herbicide selection. Greenhouse research was conducted to evaluate the response of yellow and knotroot foxtail to several turfgrass herbicides: pinoxaden (35 and 70 g ai ha−1), sethoxydim (316 and 520 g ai ha−1), thiencarbazone + dicamba + iodosulfuron (230 g ai ha−1), nicosulfuron + rimsulfuron (562.8 g ai ha−1), metribuzin (395 g ha−1), sulfentrazone (330 g ai ha−1), sulfentrazone + imazethapyr (504 g ai ha−1), and imazaquin (550 g ai ha−1). All treatments controlled yellow foxtail >87% with more than 90% reduction of the biomass. By comparison, only sulfentrazone alone controlled knotroot foxtail 90% and completely reduced aboveground biomass. Sethoxydim (520 g ai ha−1), metribuzin, and imazaquin controlled knotroot foxtail >70% at 28 d after application. In a rate response evaluation, nonlinear regression showed that yellow foxtail was approximately 8 times more susceptible to pinoxaden and 2 times more susceptible to sethoxydim than knotroot foxtail based on log (WR50) values, which were 50% reduction in fresh weight. Our research indicates that knotroot foxtail is more difficult to control across a range of herbicides, making differentiation of these two species important before herbicides are applied.

Although knowledge of their fossil record continues to improve, multituberculates nonetheless remain one of the more poorly understood mammalian clades, which can be attributed to a record comprised of isolated teeth and fragmentary jaws. Fortunately, the p4 of multituberculates is the most common form of remains for this group and is a principal source of diagnostic characters in systematic studies, the p4 of cimolodontan multituberculates is both common and a source of diagnostic characters in systematic studies. The results of a recent morphometric study on the neoplagiaulacid Mesodma suggest that p4 size may be more useful than shape in diagnosing the various species referred to this genus. We tested this hypothesis by applying two different morphometric methods (2D geometric morphometrics and linear measurements) to two samples: (1) one including the p4s of four known species of Mesodma (M. ambigua, M. thompsoni, M. formosa, and M. pygmaea), and (2) a sample of unidentified p4s of Mesodma from the Bug Creek Anthills locality of northeastern Montana. Our results indicate that while form explains most of the morphological variation in p4s of the various species of Mesodma, linear-measurement data support differences in p4 morphology that are not recovered by form data alone. Depending on the methods used, we found evidence for the presence of one or more species of Mesodma in the Bug Creek Anthills fauna. Although shape and size both contribute to morphological variation in the p4 of Mesodma, our results suggest that the diagnostic power of each varies with the type of methodology employed.

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.

The mitotic-inhibiting herbicide pronamide controls susceptible annual bluegrass (Poa annua L.) pre- and postemergence, but in some resistant populations, postemergence activity is compromised, hypothetically due to a target-site mutation, lack of root uptake, or an unknown resistance mechanism. Three suspected pronamide-resistant (LH-R, SC-R, and SL-R) and two pronamide-susceptible (BS-S and HH-S) populations were collected from Mississippi golf courses. Dose–response experiments were conducted to confirm and quantify pronamide resistance, as well as resistance to flazasulfuron and simazine. Target sites known to confer resistance to mitotic-inhibiting herbicides were sequenced, as were target sites for herbicides inhibiting acetolactate synthase (ALS) and photosystem II (PSII). Pronamide absorption and translocation were investigated following foliar and soil applications. Dose–response experiments confirmed pronamide resistance of LH-R, SC-R, and SL-R populations, as well as instances of multiple resistance to ALS- and PSII-inhibiting herbicides. Sequencing of the α-tubulin gene confirmed the presence of a mutation that substituted isoleucine for threonine at position 239 (Thr-239-Ile) in LH-R, SC-R, SL-R, and BS-S populations. Foliar application experiments failed to identify differences in pronamide absorption and translocation between the five populations, regardless of harvest time. All populations had limited basipetal translocation—only 3% to 13% of the absorbed pronamide—across harvest times. Soil application experiments revealed that pronamide translocation was similar between SC-R, SL-R, and both susceptible populations across harvest times. The LH-R population translocated less soil-applied pronamide than susceptible populations at 24, 72, and 168 h after treatment, suggesting that reduced acropetal translocation may contribute to pronamide resistance. This study reports three new pronamide-resistant populations, two of which are resistant to two modes of action (MOAs), and one of which is resistant to three MOAs. Results suggest that both target site– and translocation-based mechanisms may be associated with pronamide resistance. Further research is needed to confirm the link between pronamide resistance and the Thr-239-Ile mutation of the α-tubulin gene.

The Glasgow Composite Measure Pain Scale (CMPS) for dogs suffering acute pain, developed using psychometric methodology, measures pain to a level of precision suitable for clinical trials. However, for routine clinical use, where the emphasis is on speed, ease of use, and guidance for analgesia provision, a short form (CMPS-SF) was developed. The CMPS-SF comprises six behavioural categories with associated descriptive expressions (items): vocalisation (4), attention to wound (5), mobility (5), response to touch (6), demeanour (5) and posture/activity (5). Items are placed in increasing order of pain intensity and numbered accordingly. The observer chooses that item within each category which best describes the dog's behaviour and ranked scores are summed; the maximum pain score is 24, or 20 if mobility is impossible to assess. Veterinary surgeons in Glasgow, University College Dublin and North Carolina Veterinary Schools completed the CMPS-SF for 122 dogs undergoing post-operative care and thereafter were asked “Do you think this animal requires analgesia? Yes/No”. The population difference in median pain score, for dogs considered to require analgesia (seven) compared with those that did not (three), was highly statistically significant (P < 0.001). Consideration of a clinical decision-point for analgesia gave an intervention level of 6/24, and 5/20 when section B (mobility assessment) could not be carried out. Difficulties in recognising pain contribute to the sub-optimal use of analgesics in veterinary practice. The CMPS-SF provides a practical means of assessing acute post-operative pain and provides guidance with regard to analgesic requirement, so improving pain management and welfare. The CMPS-SF can be downloaded from the Glasgow Pain and Welfare website at http://www.gla.ac.uk/vet/painandwelfare.

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.

We formulate and solve a generalized inverse Navier–Stokes problem for the joint velocity field reconstruction and boundary segmentation of noisy flow velocity images. To regularize the problem, we use a Bayesian framework with Gaussian random fields. This allows us to estimate the uncertainties of the unknowns by approximating their posterior covariance with a quasi-Newton method. We first test the method for synthetic noisy images of two-dimensional (2-D) flows and observe that the method successfully reconstructs and segments the noisy synthetic images with a signal-to-noise ratio (SNR) of three. Then we conduct a magnetic resonance velocimetry (MRV) experiment to acquire images of an axisymmetric flow for low (${\simeq }6$) and high (${>}30$) SNRs. We show that the method is capable of reconstructing and segmenting the low SNR images, producing noiseless velocity fields and a smooth segmentation, with negligible errors compared with the high SNR images. This amounts to a reduction of the total scanning time by a factor of 27. At the same time, the method provides additional knowledge about the physics of the flow (e.g. pressure) and addresses the shortcomings of MRV (i.e. low spatial resolution and partial volume effects) that otherwise hinder the accurate estimation of wall shear stresses. Although the implementation of the method is restricted to 2-D steady planar and axisymmetric flows, the formulation applies immediately to three-dimensional (3-D) steady flows and naturally extends to 3-D periodic and unsteady flows.