We present a systematic search for radio counterparts of novae using the Australian Square Kilometer Array Pathfinder (ASKAP). Our search used the Rapid ASKAP Continuum Survey, which covered the entire sky south of declination $+41^{\circ}$ ( $\sim$ $34000$ square degrees) at a central frequency of 887.5 MHz, the Variables and Slow Transients Pilot Survey, which covered $\sim$ $5000$ square degrees per epoch (887.5 MHz), and other ASKAP pilot surveys, which covered $\sim$ 200–2000 square degrees with 2–12 h integration times. We crossmatched radio sources found in these surveys over a two–year period, from 2019 April to 2021 August, with 440 previously identified optical novae, and found radio counterparts for four novae: V5668 Sgr, V1369 Cen, YZ Ret, and RR Tel. Follow-up observations with the Australian Telescope Compact Array confirm the ejecta thinning across all observed bands with spectral analysis indicative of synchrotron emission in V1369 Cen and YZ Ret. Our light-curve fit with the Hubble Flow model yields a value of $1.65\pm 0.17 \times 10^{-4} \rm \:M_\odot$ for the mass ejected in V1369 Cen. We also derive a peak surface brightness temperature of $250\pm80$ K for YZ Ret. Using Hubble Flow model simulated radio lightcurves for novae, we demonstrate that with a 5 $\sigma$ sensitivity limit of 1.5 mJy in 15-min survey observations, we can detect radio emission up to a distance of 4 kpc if ejecta mass is in the range $10^{-3}\rm \:M_\odot$ , and upto 1 kpc if ejecta mass is in the range $10^{-5}$ – $10^{-3}\rm \:M_\odot$ . Our study highlights ASKAP’s ability to contribute to future radio observations for novae within a distance of 1 kpc hosted on white dwarfs with masses $0.4$ – $1.25\:\rm M_\odot$ , and within a distance of 4 kpc hosted on white dwarfs with masses $0.4$ – $1.0\:\rm M_\odot$ .

Carbapenem-resistant gram-negative bacilli (CR-GNB) colonization screening was initiated across high-risk departments (PICU, NICU, neonatal wards, and hematology departments) in January 2017, and several CR-GNB cohort and patient-placement strategies were introduced throughout the hospital in January 2018. The colonization and infection rates decreased to varying degrees from 2017 to 2021.

OBJECTIVES/GOALS: The goal of this study was to develop a clinically applicable technique to increase the precision of in vivo dose monitoring during radiation therapy by mapping the dose deposition and resolving the temporal dose accumulation while the treatment is being delivered in real time. METHODS/STUDY POPULATION: Ironizing radiation acoustic imaging (iRAI) is a novel imaging concept with the potential to map the delivered radiation dose on anatomic structure in real time during external beam radiation therapy without interrupting the clinical workflow. The iRAI system consisted of a custom-designed two-dimensional (2D) matrix transducer array with integrated preamplifier array, driven by a clinic-ready ultrasound imaging platform. The feasibility of iRAI volumetric imaging in mapping dose delivery and real-time monitoring of temporal dose accumulation in a clinical treatment plan were investigated with a phantom, a rabbit model, and a cancer patient. RESULTS/ANTICIPATED RESULTS: The total dose deposition and temporal dose accumulation in 3D space of a clinical C-shape treatment plan in a targeted region were first imaged and optimized in a phantom. Then, semi-quantitative iRAI measurements were achieved in an in vivo rabbit model. Finally, for the first time, real-time visualization of radiation dose delivered deep in a patient with liver metastases was performed with a clinical linear accelerator. These studies demonstrate the potential of iRAI to monitor and quantify the radiation dose deposition during treatment. DISCUSSION/SIGNIFICANCE: Described here is the pioneering role of an iRAI system in mapping the 3D radiation dose deposition of a complex clinical radiotherapy treatment plan. iRAI offers a cost-effective and practical solution for real-time visualization of 3D radiation dose delivery, potentially leading to personalized radiotherapy with optimal efficacy and safety.

A distributed UAV (unmanned aerial vehicle) flocking control method based on vision geometry is proposed, in which only monocular RGB (red, green, blue) images are used to estimate the relative positions and velocities between drones. It does not rely on special visual markers and external infrastructure, nor does it require inter-UAV communication or prior knowledge of UAV size. This method combines the advantages of deep learning and classical geometry. It adopts a deep optical flow network to estimate dense matching points between two consecutive images, uses segmentation technology to classify these matching points into background and specific UAV, and then maps the classified matching points to Euclidean space based on the depth map information. In 3D matching points, also known as 3D feature point pairs, each of their classifications is used to estimate the rotation matrix, translation vector, velocity of the corresponding UAV, as well as the relative position between drones, based on RANSAC and least squares method. On this basis, a flocking control model is constructed. Experimental results in the Microsoft Airsim simulation environment show that in all evaluation metrics, our method achieves almost the same performance as the UAV flocking algorithm based on ground truth cluster state.

As a typical plasma-based optical element that can sustain ultra-high light intensity, plasma density gratings driven by intense laser pulses have been extensively studied for wide applications. Here, we show that the plasma density grating driven by two intersecting driver laser pulses is not only nonuniform in space but also varies over time. Consequently, the probe laser pulse that passes through such a dynamic plasma density grating will be depolarized, that is, its polarization becomes spatially and temporally variable. More importantly, the laser depolarization may spontaneously take place for crossed laser beams if their polarization angles are arranged properly. The laser depolarization by a dynamic plasma density grating may find application in mitigating parametric instabilities in laser-driven inertial confinement fusion.

While conservation practices promote soil health and reduce the negative environmental effects from agricultural production, their adoption rates are generally low. To facilitate farmer adoption, we carried out a survey to identify potential challenges faced by farmers regarding conservation tillage and cover crop adoption in the western margin of the US Corn Belt. We found farmers' top two concerns regarding conservation tillage were delayed planting, caused by slow soil warming in spring, and increased dependence on herbicide and fungicides. Narrow planting window and lack of time/labor were perceived by farmers as the two primary challenges for cover crop adoption. Some sense of place factors, including the commonly included dimensions of attachment, identity and dependence, played a role in farmers' perceived challenges. For example, respondents more economically dependent on farming perceived greater challenges. We found that farmers' challenge perceptions regarding reduced yield and lack of time/labor significantly decreased as years of usage increased, implying that time and experience could dilute some challenges faced by farmers. Our findings indicate that social network use, technical guidance and economic subsidies are likely to address the concerns of farmers and facilitate their adoption of conservation practices.

Meat quality is not only influenced by breed but also rearing environment. The aim of this study was to evaluate the influence of different housing environments on growth performance, carcase traits, meat quality, physiological response pre-slaughter and fatty acid composition in two pig breeds. A total of 120 growing pigs at 60-70 days of age were arranged in a 2 × 2 factorial design with the breeds (Duroc × Landrace × Large White [D × L × LW] and Duroc × Landrace × Min pig [D × L × M]) and environmental enrichment (barren concrete floor or enriched with straw bedding) as factors. Each treatment was performed in triplicate with ten pigs per replicate. The pigs housed in the enriched environment exhibited a higher average daily gain, average daily feed intake, saturated fatty acid percentage and backfat depth than the pigs reared in the barren environment. Plasma cortisol levels were lower and growth hormone higher in enriched compared to barren pens. The D × L × M pigs showed lower cooking loss compared with the D × L × LW pigs. Moreover, the D × L × M pigs exhibited poor growth performance but had a better water-holding capacity. Only carcase traits and meat quality interaction effects were observed. We concluded that an enriched environment can reduce preslaughter stress and improve the growth performance of pigs and modulate the fatty acid composition of pork products.

COVID-19 changed the landscape of employment and financial security in the USA, contributing to multi-systemic disruptions in family life. Using dyadic, daily-diary parent–adolescent data from a nationwide American sample (18,415 daily assessments; 29 days: 4/8/2020–4/21/2020 and 5/18/2020–6/1/2020; N = 635 parent–adolescent dyads), this intensive longitudinal study investigated how COVID-19-related job loss and working-from-home (WFH) arrangements influenced parents’ and children’s daily affect indirectly through family functioning (i.e., parent–adolescent conflict, inter-adult conflict, and parental warmth) and whether these links varied by family socioeconomic status (SES). Parental employment status was linked to these family relational dynamics, which were then connected to parents’ and adolescents’ daily affect. Although SES did not moderate these links, low-income families were more likely to experience job loss, parent–adolescent conflict, and inter-adult conflict and less likely to WFH than higher-income families. As inter-relations within the family are a malleable point for intervention, clinicians working with families recovering from the fiscal impact of the COVID-19 pandemic are encouraged to use approaches that strengthen family relationships, especially between adolescents and their parents. Unemployment subsidies are discussed as a means to support families struggling with job loss, and organizations are urged to consider the benefits of WFH on employee health and work-life balance.

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 present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60\,\mathrm{deg}^{2}$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of $z \lesssim 0.08$ . The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of $z \approx 0.014$ is relatively low compared to the full WALLABY survey. The median galaxy H i mass is $2.3 \times 10^{9}\,{\rm M}_{{\odot}}$ . The target noise level of $1.6\,\mathrm{mJy}$ per 30′′ beam and $18.5\,\mathrm{kHz}$ channel translates into a $5 \sigma$ H i mass sensitivity for point sources of about $5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$ across 50 spectral channels ( ${\approx} 200\,\mathrm{km \, s}^{-1}$ ) and a $5 \sigma$ H i column density sensitivity of about $8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$ across 5 channels ( ${\approx} 20\,\mathrm{km \, s}^{-1}$ ) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.

Loss functions with a large number of saddle points are one of the major obstacles for training modern machine learning (ML) models efficiently. First-order methods such as gradient descent (GD) are usually the methods of choice for training ML models. However, these methods converge to saddle points for certain choices of initial guesses. In this paper, we propose a modification of the recently proposed Laplacian smoothing gradient descent (LSGD) [Osher et al., arXiv:1806.06317], called modified LSGD (mLSGD), and demonstrate its potential to avoid saddle points without sacrificing the convergence rate. Our analysis is based on the attraction region, formed by all starting points for which the considered numerical scheme converges to a saddle point. We investigate the attraction region’s dimension both analytically and numerically. For a canonical class of quadratic functions, we show that the dimension of the attraction region for mLSGD is $\lfloor (n-1)/2\rfloor$ , and hence it is significantly smaller than that of GD whose dimension is $n-1$ .

Since 2014, Chinese courts have placed tens of millions of court judgments online. We analyze the promise and pitfalls of using this new data source, highlighting takeaways for readers facing similar issues using other collections of legal texts. Drawing on 1,058,986 documents from Henan Province, we identify problems with missing data and call on scholars to treat variation in court disclosure rates as an urgent research question. We also outline strategies for learning from a corpus that is vast and incomplete. Using a topic model of administrative litigation in Henan, we complicate conventional wisdom that administrative lawsuits are an extension of contentious politics that give Chinese citizens an opportunity to challenge the state. Instead, we find a high prevalence of administrative cases that reflect an underlying dispute between two private parties, suggesting that administrative lawsuits are often an attempt to enlist help from the state in resolving an underlying civil dispute.

During the current global COVID-19 crisis Taiwan has portrayed itself as both an example for other countries to follow and as a country willing to assist others in their own efforts with the virus. Taiwan has also renewed efforts to participate in the World Health Organization (WHO), an organisation from which it is currently excluded. Although some countries have supported Taiwan's efforts to participate in the WHO or have praised its COVID-19 response, others have been silent or even critical, sometimes citing commitments to a “one China policy.” In this paper, we use newly collected data to explore cross-national variation in support for Taiwan during the current pandemic. We find that a country's level of economic development and security ties with the US are strongly correlated with support for Taiwan while a country's economic ties to China is a less consistent predictor.