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We present the final 6'' resolution data release of the ELAIS-N1 field from the LOw-Frequency ARray (LOFAR) Two-metre Sky Survey Deep Fields project (LoTSS Deep). The 144MHz images are the most sensitive achieved to date at this frequency and were created from 290 TB of data obtained from 505 hrs on-source observations taken over 7.5 years. The data were processed following the strategies developed for previous LoTSS and LoTSS Deep data releases. The resulting images span 24.53 square degrees and, using a refined source detection approach, we identified 154,952 radio sources formed from 182,184 Gaussian components within this area. The maps reach a noise level of 10.7 $\mu$Jy/beam at 6'' resolution where approximately half of the noise is due to source confusion. In about 7.4% of the image our limited dynamic range around bright sources results in a further > 5% increase in the noise. The images have a flux density scale accuracy of about 9% and the standard deviation of offsets between our source positions and those from Pan-STARRS is 0.2'' in RA and Dec for high significance detections. We searched individual epoch images for variable sources, identifying 39 objects with considerable variation. We also searched for circularly polarised sources achieving three detections of previously known emitters (two stars and one pulsar) whilst constraining the typical polarisation fraction plus leakage to be less than 0.045%., Comment: Accepted for publication in A&A. 16 figures, 1 table and 20 pages. The catalogues and images associated with this data release are publicly available via https://lofar-surveys.org/

This paper introduces a closed-form analytical solution for the inverse kinematics (IK) of a 6 Degrees of Freedom (DOF) serial robotic manipulator arm, configured with six revolute joints and utilized within the Lunar Exploration Rover System (LERS). As a critical asset for conducting precise operations in the demanding lunar environment, this robotic arm relies on the IK solution to determine joint parameters required for precise end-effector positioning, essential for tasks such as sample collection, infrastructure assembly, and equipment deployment. By applying geometric principles, the proposed method offers a highly efficient and accurate approach to solving the IK problem, significantly reducing computational demands compared to traditional numerical methods. This advancement not only enhances real-time operational capabilities but is also optimized for space robotics, where precision and speed are critical. Additionally, the paper explores the integration of the LERS robotic system, underscoring the importance of this work in supporting autonomous lunar exploration within the ARTEMIS program and future missions, Comment: 9 pages, 7 figures

Turn-taking is a fundamental mechanism in human communication that ensures smooth and coherent verbal interactions. Recent advances in Large Language Models (LLMs) have motivated their use in improving the turn-taking capabilities of Spoken Dialogue Systems (SDS), such as their ability to respond at appropriate times. However, existing models often struggle to predict opportunities for speaking -- called Transition Relevance Places (TRPs) -- in natural, unscripted conversations, focusing only on turn-final TRPs and not within-turn TRPs. To address these limitations, we introduce a novel dataset of participant-labeled within-turn TRPs and use it to evaluate the performance of state-of-the-art LLMs in predicting opportunities for speaking. Our experiments reveal the current limitations of LLMs in modeling unscripted spoken interactions, highlighting areas for improvement and paving the way for more naturalistic dialogue systems., Comment: EMNLP 2024 (Findings)

Recent observations have revealed rare, previously unknown flashes of cosmic radio waves lasting from milliseconds to minutes, and with periodicity of minutes to an hour [1-4]. These transient radio signals must originate from sources in the Milky Way, and from coherent emission processes in astrophysical plasma. They are theorised to be produced in the extreme and highly magnetised environments around white dwarfs or neutron stars [5-8]. However, the astrophysical origin of these signals remains contested, and multiple progenitor models may be needed to explain their diverse properties. Here we present the discovery of a transient radio source, ILT J1101+5521, whose roughly minute-long pulses arrive with a periodicity of 125.5 minutes. We find that ILT J1101+5521 is an M dwarf - white dwarf binary system with an orbital period that matches the period of the radio pulses, which are observed when the two stars are in conjunction. The binary nature of ILT J1101+5521 establishes that some long-period radio transients originate from orbital motion modulating the observed emission, as opposed to an isolated rotating star. We conclude that ILT J1101+5521 is likely a polar system where magnetic interaction has synchronised the rotational and orbital periods of the white dwarf [9]. Magnetic interaction and plasma exchange between the two stars may generate the sporadic radio emission. Such mechanisms have been previously theorised [10-13], but not observationally established.

The collision avoidance constraints are prominent as non-convex, non-differentiable, and challenging when defined in optimization-based motion planning problems. To overcome these issues, this paper presents a novel non-conservative collision avoidance technique using the notion of convex optimization to establish the distance between robotic spacecraft and space structures for autonomous on-orbit assembly operations. The proposed technique defines each ellipsoidal- and polyhedral-shaped object as the union of convex compact sets, each represented non-conservatively by a real-valued convex function. Then, the functions are introduced as a set of constraints to a convex optimization problem to produce a new set of differentiable constraints resulting from the optimality conditions. These new constraints are later fed into an optimal control problem to enforce collision avoidance where the motion planning for the autonomous on-orbit assembly takes place. Numerical experiments for two assembly scenarios in tight environments are presented to demonstrate the capability and effectiveness of the proposed technique. The results show that this framework leads to optimal non-conservative trajectories for robotic spacecraft in tight environments. Although developed for autonomous on-orbit assembly, this technique could be used for any generic motion planning problem where collision avoidance is crucial., Comment: Technical Note version of this paper is under review in the Journal of Guidance, Control, and Dynamics (JGCD), revision submitted in April 2024

Compound flooding, where the combination or successive occurrence of two or more flood drivers leads to an extreme impact, can greatly exacerbate the adverse consequences associated with flooding in coastal regions. This paper reviews the practices and trends in coastal compound flood research methodologies and applications, as well as synthesizes key findings at regional and global scales. Systematic review is employed to construct a literature database of 271 studies relevant to compound flood hazards in a coastal context. This review explores the types of compound flood events, their mechanistic processes, and synthesizes the definitions and terms exhibited throughout the literature. Considered in the review are six flood drivers (fluvial, pluvial, coastal, groundwater, damming/dam failure, and tsunami) and five precursor events and environmental conditions (soil moisture, snow, temp/heat, fire, and drought). Furthermore, this review summarizes the trends in research methodology, examines the wide range of study applications, and considers the influences of climate change and urban environments. Finally, this review highlights the knowledge gaps in compound flood research and discusses the implications of review findings on future practices. Our five recommendations for future compound flood research are to: 1) adopt consistent definitions, terminology, and approaches; 2) expand the geographic coverage of research; 3) pursue more inter-comparison projects; 4) develop modelling frameworks that better couple dynamic earth systems; and 5) design urban and coastal infrastructure with compound flooding in mind. We hope this review will help to enhance understanding of compound flooding, guide areas for future research focus, and close knowledge gaps., Comment: 95 pages (Main Text 3-59, References 61-77, Appendix 77-95), 7 figures

The latest X-ray photon-counting computed tomography (PCCT) for extremity allows multi-energy high-resolution (HR) imaging for tissue characterization and material decomposition. However, both radiation dose and imaging speed need improvement for contrast-enhanced and other studies. Despite the success of deep learning methods for 2D few-view reconstruction, applying them to HR volumetric reconstruction of extremity scans for clinical diagnosis has been limited due to GPU memory constraints, training data scarcity, and domain gap issues. In this paper, we propose a deep learning-based approach for PCCT image reconstruction at halved dose and doubled speed in a New Zealand clinical trial. Particularly, we present a patch-based volumetric refinement network to alleviate the GPU memory limitation, train network with synthetic data, and use model-based iterative refinement to bridge the gap between synthetic and real-world data. The simulation and phantom experiments demonstrate consistently improved results under different acquisition conditions on both in- and off-domain structures using a fixed network. The image quality of 8 patients from the clinical trial are evaluated by three radiologists in comparison with the standard image reconstruction with a full-view dataset. It is shown that our proposed approach is essentially identical to or better than the clinical benchmark in terms of diagnostic image quality scores. Our approach has a great potential to improve the safety and efficiency of PCCT without compromising image quality., Comment: 9 figures, 5 tables

How political beliefs change in accordance with media exposure is a complicated matter. Some studies have been able to demonstrate that groups with different media diets in the aggregate (e.g., U.S. media consumers ingesting partisan news) arrive at different beliefs about policy issues, but proving this from data at a granular level -- at the level of attitudes expressed in news stories -- remains difficult. In contrast to existing opinion formation models that describe granular detail but are not data-driven, or data-driven studies that rely on simple keyword detection and miss linguistic nuances, being able to identify complicated attitudes in news text and use this data to drive models would enable more nuanced empirical study of opinion formation from media messaging. This study contributes a dataset as well as an analysis that allows the mapping of attitudes from individual news stories to aggregate changes of opinion over time for an important public health topic where opinion differed in the U.S. by partisan media diet: Covid mask-wearing beliefs. By gathering a dataset of U.S. news media stories, from April 6 to June 8, 2020, annotated according to Howard 2020's Face Mask Perception Scale for their statements regarding Covid-19 mask-wearing, we demonstrate fine-grained correlations between media messaging and empirical opinion polling data from a Gallup survey conducted during the same period. We also demonstrate that the data can be used for quantitative analysis of pro- and anti-mask sentiment throughout the period, identifying major events that drove opinion changes. This dataset is made publicly available and can be used by other researchers seeking to evaluate how mask-wearing attitudes were driven by news media content. Additionally, we hope that its general method can be used to enable other media researchers to conduct more detailed analyses of media effects on opinion.

In this paper, we present rapid follow-up observations of the short GRB 201006A, consistent with being a compact binary merger, using the LOw Frequency ARray (LOFAR). We have detected a candidate 5.6$\sigma$, short, coherent radio flash at 144 MHz at 76.6 mins post-GRB with a 3$\sigma$ duration of 38 seconds. This radio flash is 27 arcsec offset from the GRB location, which has a probability of occurring by chance of $\sim$0.05% (3.8$\sigma$) when accounting for measurement uncertainties. Despite the offset, we show that the probability of finding an unrelated transient within 40 arcsec of the GRB location is $<10^{-6}$ and conclude that this is a candidate radio counterpart to GRB 201006A. We performed image plane dedispersion and the radio flash is tentatively (2.4$\sigma$) shown to be highly dispersed, allowing a distance estimate, corresponding to a redshift of $0.58\pm0.06$. The corresponding luminosity of the event at this distance is $6.7^{+6.6}_{-4.4} \times 10^{32}$ erg s$^{-1}$ Hz$^{-1}$. If associated with GRB 201006A, this emission would indicate prolonged activity from the central engine that is consistent with being a newborn, supramassive, likely highly magnetised, millisecond spin neutron star (a magnetar)., Comment: MNRAS Accepted

We present a search for transient radio sources on time-scales of seconds to hours at 144 MHz using the LOFAR Two-metre Sky Survey (LoTSS). This search is conducted by examining short time-scale images derived from the LoTSS data. To allow imaging of LoTSS on short time-scales, a novel imaging and filtering strategy is introduced. This includes sky model source subtraction, no cleaning or primary beam correction, a simple source finder, fast filtering schemes and source catalogue matching. This new strategy is first tested by injecting simulated transients, with a range of flux densities and durations, into the data. We find the limiting sensitivity to be 113 and 6 mJy for 8 second and 1 hour transients respectively. The new imaging and filtering strategies are applied to 58 fields of the LoTSS survey, corresponding to LoTSS-DR1 (2% of the survey). One transient source is identified in the 8 second and 2 minute snapshot images. The source shows one minute duration flare in the 8 hour observation. Our method puts the most sensitive constraints on/estimates of the transient surface density at low frequencies at time-scales of seconds to hours; $<4.0\cdot 10^{-4} \; \text{deg}^{-2}$ at 1 hour at a sensitivity of 6.3 mJy; $5.7\cdot 10^{-7} \; \text{deg}^{-2}$ at 2 minutes at a sensitivity of 30 mJy; and $3.6\cdot 10^{-8} \; \text{deg}^{-2}$ at 8 seconds at a sensitivity of 113 mJy. In the future, we plan to apply the strategies presented in this paper to all LoTSS data., Comment: submitted to MNRAS

The composition of relativistic gamma-ray burst (GRB) jets and their emission mechanisms are still debated, and they could be matter or magnetically dominated. One way to distinguish these mechanisms arises because a Poynting flux dominated jet may produce low-frequency radio emission during the energetic prompt phase, through magnetic reconnection at the shock front. We present a search for radio emission coincident with three GRB X-ray flares with the LOw Frequency ARray (LOFAR), in a rapid response mode follow-up of long GRB 210112A (at z~2) with a 2 hour duration, where our observations began 511 seconds after the initial swift-BAT trigger. Using timesliced imaging at 120-168 MHz, we obtain upper limits at 3 sigma confidence of 42 mJy averaging over 320 second snapshot images, and 87 mJy averaging over 60 second snapshot images. LOFAR's fast response time means that all three potential radio counterparts to X-ray flares are observable after accounting for dispersion at the estimated source redshift. Furthermore, the radio pulse in the magnetic wind model was expected to be detectable at our observing frequency and flux density limits which allows us to disfavour a region of parameter space for this GRB. However, we note that stricter constraints on redshift and the fraction of energy in the magnetic field are required to further test jet characteristics across the GRB population., Comment: 13 pages, 7 figures, accepted for publication in MNRAS

Transient surveys are a vital tool in exploring the dynamic universe, with radio transients acting as beacons for explosive and highly energetic astrophysical phenomena. However, performing commensal transient surveys using radio imaging can require a significant amount of computing power, data storage and time. With the instrumentation available to us, and with new and exciting radio interferometers in development, it is essential that we develop efficient methods to probe the radio transient sky. In this paper, we present results from an commensal short duration transient survey, on time scales of 8 seconds, 128 seconds and 1 hour, using data from the MeerKAT radio telescope. The dataset used was obtained as part of a galaxy observing campaign, and we focus on the field of NGC 5068. We present a quick, wide field imaging strategy to enable fast imaging of large datasets, and develop methods to efficiently filter detected transient candidates. No transient candidates were identified on the time scales of 8 seconds, 128 seconds and 1 hour, leading to competitive limits on the transient surface densities of $6.7{\times}10^{-5}$ deg$^{-1}$, $1.1{\times}10^{-3}$ deg$^{-1}$, and $3.2{\times}10^{-2}$ deg$^{-1}$ at sensitivities of 56.4 mJy, 19.2 mJy, and 3.9 mJy for the respective time scales. We find one possible candidate that could be associated with a stellar flare, that was rejected due to strict image quality control. Further short time-scale radio observations of this candidate could give definite results to its origin., Comment: 11 pages (9 main, 2 appendix), 8 figures, 2 tables. Submitted to MNRAS

From 08-12 August, 2022, 32 individuals participated in a workshop, Stability and Fluctuations in Complex Ecological Systems, at the Lorentz Center, located in Leiden, The Netherlands. An interdisciplinary dialogue between ecologists, mathematicians, and physicists provided a foundation of important problems to consider over the next 5-10 years. This paper outlines eight areas including (1) improving our understanding of the effect of scale, both temporal and spatial, for both deterministic and stochastic problems; (2) clarifying the different terminologies and definitions used in different scientific fields; (3) developing a comprehensive set of data analysis techniques arising from different fields but which can be used together to improve our understanding of existing data sets; (4) having theoreticians/computational scientists collaborate closely with empirical ecologists to determine what new data should be collected; (5) improving our knowledge of how to protect and/or restore ecosystems; (6) incorporating socio-economic effects into models of ecosystems; (7) improving our understanding of the role of deterministic and stochastic fluctuations; (8) studying the current state of biodiversity at the functional level, taxa level and genome level., Comment: 22 pages

Nanocomposite membranes are an emerging filtration material in the production of clean water. Recently, the fabrication of porous nanocomposite membranes via solvent transfer induced phase separation (STrIPS) was introduced. During STrIPS, the phase separation of two immiscible liquids is arrested by the attachment of nanoparticles at the liquid-liquid interface, generating a porous particle-stabilized membrane template. STrIPS nanocomposite membranes, however, have so far only been produced as hollow fibers. To overcome this, we designed a roll-to-roll (R2R)-process for the continuous fabrication of flat-sheet nanocomposite membranes via STrIPS. We produce the STrIPS membrane by printing the membrane precursor on a carrier substrate. This allows for the continuous collection of STrIPS membranes with control over the membrane dimensions. Contact angle measurements elucidate the wetting dynamics of the STrIPS membrane on the substrate. Furthermore, we demonstrate control over the membrane pore structure by varying the precusor liquid composition and by changing the particle modification and loading in the membrane. With this, the R2R-approach may stimulate further advancements in the fabrication of flat-sheet nanocomposite membranes via STrIPS., Comment: 26 pages, 15 figures

We report low-frequency radio observations of the 2021 outburst of the recurrent nova RS Ophiuchi. These observations include the lowest frequency observations of this system to date. Detailed light curves are obtained by MeerKAT at 0.82 and 1.28 GHz and LOFAR at 54 and 154 MHz. These low-frequency detections allow us to put stringent constraints on the brightness temperature that clearly favour a non-thermal emission mechanism. The radio emission is interpreted and modelled as synchrotron emission from the shock interaction between the nova ejecta and the circumbinary medium. The light curve shows a plateauing behaviour after the first peak, which can be explained by either a non-uniform density of the circumbinary medium or a second emission component. Allowing for a second component in the light-curve modelling captures the steep decay at late times. Furthermore, extrapolating this model to 15 yr after the outburst shows that the radio emission might not fully disappear between outbursts. Further modelling of the light curves indicates a red giant mass-loss rate of $\sim 5 \cdot 10^{-8}~{\rm M_\odot~yr^{-1}}$. The spectrum cannot be modelled in detail at this stage, as there are likely at least four emission components. Radio emission from stellar wind or synchrotron jets is ruled out as the possible origin of the radio emission. Finally, we suggest a strategy for future observations that would advance our understanding of the physical properties of RS Ophiuchi., Comment: Published in MNRAS