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In the 21st century, education has become America's most significant marker of class privilege. People with bachelor's and advanced degrees have mostly prospered, while wages for those with less education have fallen. This divergence in economic fortunes lies at the heart of our country's present economic and political discontents. Federal and state policies remain strongly biased in favor of subsidies to Americans who go to college, specifically those who acquire a 4-year degree. The nation's chronic underinvestment in work-related learning, experiences, and supports is not just unjust, it is bad economics. It squanders our most precious resource -- our workers -- and subtracts from U.S. productivity growth and competitiveness. American workers deserve better than a binary choice between an overpriced college degree program and a patchwork of public and private job training programs of uneven quality. Instead, U.S. leaders should equalize opportunity for workers, regardless of what path they choose. This means building a world-class education system that is inclusive of all options, not just college, to ensure greater upward mobility for American workers. This report is the first in a series of Campaign Blueprints detailing new ideas that can help Democrats reach across today's yawning "diploma divide" and reconnect with the working-class voters who have historically been the party's mainstay.

DarkSide-20k is a novel liquid argon dark matter detector currently under construction at the Laboratori Nazionali del Gran Sasso (LNGS) of the Istituto Nazionale di Fisica Nucleare (INFN) that will push the sensitivity for Weakly Interacting Massive Particle (WIMP) detection into the neutrino fog. The core of the apparatus is a dual-phase Time Projection Chamber (TPC), filled with \SI{50} {tonnes} of low radioactivity underground argon (UAr) acting as the WIMP target. NUV-HD-Cryo Silicon Photomultipliers (SiPM)s designed by Fondazione Bruno Kessler (FBK) (Povo, Trento, Italy) were selected as the photon sensors covering two $10.5~\text{m}^2$ Optical Planes, one at each end of the TPC, and a total of $5~\text{m}^2$ photosensitive surface for the liquid argon veto detectors. This paper describes the Quality Assurance and Quality Control (QA/QC) plan and procedures accompanying the production of FBK~NUV-HD-Cryo SiPM wafers manufactured by LFoundry s.r.l. (Avezzano, AQ, Italy). SiPM characteristics are measured at 77~K at the wafer level with a custom-designed probe station. As of May~2024, 603 of the 1400 production wafers (43\% of the total) for DarkSide-20k were tested, including wafers from all 57 production Lots. The wafer yield is $93.6\pm2.5$\%, which exceeds the 80\% specification defined in the original DarkSide-20k production plan.

Pulsar timing array observations have found evidence for an isotropic gravitational wave background with the Hellings-Downs angular correlations, expected from general relativity. This interpretation hinges on the measured shape of the angular correlations, which is predominately quadrupolar under general relativity. Here we explore a more flexible parameterization: we expand the angular correlations into a sum of Legendre polynomials and use a Bayesian analysis to constrain their coefficients with the 15-year pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). When including Legendre polynomials with multipoles $\ell \geq 2$, we only find a significant signal in the quadrupole with an amplitude consistent with general relativity and non-zero at the $\sim 95\%$ confidence level and a Bayes factor of 200. When we include multipoles $\ell \leq 1$, the Bayes factor evidence for quadrupole correlations decreases by more than an order of magnitude due to evidence for a monopolar signal at approximately 4 nHz which has also been noted in previous analyses of the NANOGrav 15-year data. Further work needs to be done in order to better characterize the properties of this monopolar signal and its effect on the evidence for quadrupolar angular correlations., Comment: 15 pages, 6 figures

The detection of a stochastic gravitational wave background by pulsar timing arrays suggests the presence of a supermassive black hole binary population. Although the observed spectrum generally aligns with predictions from orbital evolution driven by gravitational wave emission in circular orbits, there is a discernible preference for a turnover at the lowest observed frequencies. This turnover could indicate a significant hardening phase, transitioning from early environmental influences to later stages predominantly influenced by gravitational wave emission. In the vicinity of these binaries, the ejection of stars or dark matter particles through gravitational three-body slingshots efficiently extracts orbital energy, leading to a low-frequency turnover in the spectrum. By analyzing the NANOGrav 15-year data, we assess how the gravitational wave spectrum depends on the initial inner galactic profile prior to disruption by binary ejections, accounting for a range of initial binary eccentricities. Our findings suggest a parsec-scale galactic center density around $10^6\,M_\odot/\textrm{pc}^3$ across most of the parameter space, offering insights into the environmental effects on black hole evolution and combined matter density near galaxy centers., Comment: 15 pages, 5 figures

There is substantial variation in the returns to a college degree. One determinant is whether a worker's employment is "matched" with their education. With a novel education-industry crosswalk and panel data on 295,000 graduates, we provide the first estimates of an education-industry match premium leveraging within-person variation in earnings. We document which majors have the most and least matching, how earnings premia vary across fields and gender, and how premia evolve over time. With robust estimators, we show that workers in industries "matched" with their degree experience an average earnings premium of 7-11%, with variation by degree level and major.

This paper presents a rationale for using professional and continuing education (PaCE) units at post-secondary institutions throughout California to design and implement talent-pipelines, research and development collaborations, and other knowledge ecosystems where emerging and returning professionals can acquire the knowledge, skills, and abilities (KSAs), as well as the experience, they need to address the challenges of the Fourth Industrial Revolution (4IR). The paper provides an analysis of the reasons why PaCE units are uniquely positioned to address the needs of industry and job seekers, and on a timetable that keeps pace with 4IR velocity.

America's labor market presents a paradox. Although the unemployment rate is just 3.9%, there are more jobs open than people who can fill them. Nationwide, there are roughly 68 workers for every 100 open jobs. Many factors contribute to this workforce shortage, but one of the most significant is a growing skills gap -- millions of workers across the economy are unprepared for in-demand employment opportunities. In construction and other industries, employers are hurting, desperate for talent, and looking for innovative ways to attract people to open positions. Recent data from the Bureau of Labor Statistics (BLS) show that the construction industry currently has 407,000 job openings. This shortage is expected to grow, with a projected need for 723,000 workers annually due to economic expansion, worker retirements, and the changing skill needs driven by energy transitions and technological advancements. Some 88% of construction firms report having a hard time finding workers to hire. To address this challenge, employers in construction and other industries are investing in workforce development -- working to ensure current and future workers have the skills needed to succeed in high-demand careers. But employers can't do it alone. And although federal funding is available to support skill development, it is not nearly enough. Just $28.2 billion out of a total $139.5 billion allocated annually for postsecondary education and training is spent on workforce development. This policy brief estimates current federal spending on postsecondary workforce education and training and compares these funding levels to funding for traditional academic programs. This brief explores how investment in workforce education today compares to in investment in recent decades. Finally, it offers examples of how four states are investing in workforce education and offers policy recommendations for stakeholders and policymakers to consider for the future. [This report was co-produced by Procore with support from the Construction Advocacy Fund.]

Attracting and retaining high-quality teachers is a pressing policy concern. Increasing teacher salaries and creating more attractive compensation packages are often proposed as a potential solution. Signed into law in March 2023, the LEARNS Act increased Arkansas's minimum teacher salary from $36,000 to $50,000, guaranteed all teachers a minimum raise of $2,000, and added flexibility allowing school districts to deviate from seniority-based traditional salary schedules. To study school districts' adjustments to the new legislation, we collected information about districts' teacher compensation policies one year before and the first year of implementation. We also integrated this data with teachers' administrative records to study patterns of teacher retention and mobility. Our results reveal a more equitable distribution of starting teacher salaries across districts, with minimal variation. The LEARNS Act notably increased funding for rural and high-poverty districts, mitigating the negative association between starting salaries and district poverty rates. However, the initial effects on teacher retention and mobility were modest. While some positive trends emerged, such as reduced probabilities of teachers transitioning to non-instructional roles and increased new teacher placement in geographic areas of shortage, broader impacts on retention and mobility were limited in the first year of implementation.

Research for Action (RFA) in partnership with the University of Texas at Austin is engaged in a five-year mixed-methods study of the reforms associated with California AB 705. Over the course of the study, our team will assess the implementation, impact, and cost effectiveness of reforms associated with the law. This second interim report, presented at the conclusion of year three of the study, focuses on gaining a deeper understanding of on-campus implementation through a faculty survey administered to math and English departments across our study sample, an Interrupted Time Series analysis with nine cohorts of FTIC student data, and preliminary data collection for our cost effectiveness study. Collectively, these data highlight significant changes that colleges have made on campus regarding shifting enrollments from developmental education into transfer-level coursework in both English and math, and providing additional supports to students to promote retention and completion. We find that AB 705 has demonstrated notable successes in improving enrollment and completion rates in transfer-level courses, particularly in math, among FTIC students in California's community colleges. While our survey results suggest that faculty believe additional resources and supports would be helpful, most faculty report that implementation supports have been adequate.

When employees expect evaluation and performance incentives will continue (or begin) in the future, the potential future rewards create an incentive to invest in relevant skills today. Because skills benefit job performance, the effects of evaluation can persist after the rewards end or even anticipate the start of rewards. I provide empirical evidence of these dynamics from a quasi-experiment in Tennessee schools. New performance measures improve teachers' value-added contributions to student achievement. But improvements are twice as large when the teacher also expects future rewards linked to future scores. Value-added remains at the now higher level after performance incentives end.

We generalise the Kugo and Ojima formalism henceforth called KO) for the structure of state space in gauge theories, in four respects:- (i) We allow for a more general class of gauge-fixing including non-covariant cases. (ii) We display the two possible Hamiltonians allowed by the KO action. (iii) We give manifestly Lorentz invariant forms of KO, showing that they are not unique. (iv) We analyse the structure of Fock space, proving that the allowed states span exactly half of it (leaving aside pure transverse states)., Comment: 12 pages

Social skills training targets behaviors necessary for success in social interactions. However, traditional classroom training for such skills is often insufficient to teach effective communication -- one-to-one interaction in real-world scenarios is preferred to lecture-style information delivery. This paper introduces a framework that allows instructors to collaborate with large language models to dynamically design realistic scenarios for students to communicate. Our framework uses these scenarios to enable student rehearsal, provide immediate feedback, and visualize performance for both students and instructors. Unlike traditional intelligent tutoring systems, instructors can easily co-create scenarios with a large language model without technical skills. Additionally, the system generates new scenario branches in real time when existing options do not fit the student's response.

INTRODUCTION: Wikipedia is a major source of information, particularly for medical and health content, citing over 4 million scholarly publications. However, the representation of research-based knowledge across different languages on Wikipedia has been under explored. This study analyses the largest database of Wikipedia citations collected to date, examining the uniqueness of content and research representation across languages. METHOD: The study included nearly 3.5 million unique research articles and their Wikipedia mentions from 21 languages. These were categorized into three groups: Group A (publications uniquely cited by a single non-English Wikipedia), Group B (co-cited by English and non-English Wikipedias), and Group C (co-cited by multiple non-English Wikipedias). Descriptive and comparative statistics were conducted by Wikipedia language, group, and discipline. RESULTS: Significant differences were found between twenty non-English languages and English Wikipedia (p<0.001). While English Wikipedia is the largest, non-English Wikipedias cite an additional 1.5 million publications. CONCLUSION: English Wikipedia should not be seen as a comprehensive body of information. Non-English Wikipedias cover unique subjects and disciplines, offering a more complete representation of research collectively. The uniqueness of voice in non-English Wikipedias correlates with their size, though other factors may also influence these differences.

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

Cosmological information is encoded in the structure of galaxy clusters. In Universes with less matter and larger initial density perturbations, clusters form earlier and have more time to accrete material, leading to a more extended infall region. Thus, measuring the mean mass distribution in the infall region provides a novel cosmological test. The infall region is largely insensitive to baryonic physics, and provides a cleaner structural test than other measures of cluster assembly time such as concentration. We consider cluster samples from three publicly available galaxy cluster catalogues: the Spectrsopic Identification of eROSITA Sources (SPIDERS) catalogue, the X-ray and Sunyaev-Zeldovich effect selected clusters in the meta-catalogue M2C, and clusters identified in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Survey. Using a preliminary shape catalogue from the Ultraviolet Near Infrared Optical Northern Survey (UNIONS), we derive excess surface mass density profiles for each sample. We then compare the mean profile for the DESI Legacy sample, which is the most complete, to predictions from a suite of simulations covering a range of $\Omega_{\rm m}$ and $\sigma_8$, obtaining constraints of $\Omega_{\rm m}=0.29\pm 0.05$ and $\sigma_8=0.80 \pm 0.04$. We also measure mean (comoving) splashback radii for SPIDERS, M2C and DESI Legacy Imaging Survey clusters of $1.59^{+0.16}_{-0.13} {\rm cMpc}/h$, $1.30^{+0.25}_{-0.13} {\rm cMpc}/h$ and $1.45\pm0.11 {\rm cMpc}/h$ respectively. Performing this analysis with the final UNIONS shape catalogue and the full sample of spectroscopically observed clusters in DESI, we can expect to improve on the best current constraints from cluster abundance studies by a factor of 2 or more., Comment: 16 pages, 10 figures. Submitted to MNRAS

Data from the Euclid space telescope will enable cosmic shear measurements with very small statistical errors, requiring corresponding systematic error control level. A common approach to correct for shear biases involves calibrating shape measurement methods using image simulations with known input shear. Given their high resolution, Hubble Space Telescope (HST) galaxies can, in principle, be utilised to emulate Euclid observations. In this work, we employ a GalSim-based testing environment to investigate whether uncertainties in the HST point spread function (PSF) model or in data processing techniques introduce significant biases in weak-lensing (WL) shear calibration. We used single S\'ersic galaxy models to simulate both HST and Euclid observations. We then `Euclidised' our HST simulations and compared the results with the directly simulated Euclid-like images. For this comparison, we utilised a moment-based shape measurement algorithm and galaxy model fits. Through the Euclidisation procedure, we effectively reduced the residual multiplicative biases in shear measurements to sub-percent levels. This achievement was made possible by employing either the native pixel scales of the instruments, utilising the Lanczos15 interpolation kernel, correcting for noise correlations, and ensuring consistent galaxy signal-to-noise ratios between simulation branches. However, the Euclidisation procedure requires further analysis on the impact of the correlated noise, to estimate calibration bias. Additionally, we conducted an in-depth analysis of the accuracy of TinyTim HST PSF models using star fields observed in the F606W and F814W filters. We observe that F606W images exhibit a broader scatter in the recovered best-fit focus, compared to those in the F814W filter., Comment: Accepted by A&A. 23 pages, 20 figures, Euclid pre-launch key paper

We present a simulation-based method to explore the optimum tomographic redshift binning strategy for 3x2pt analyses with Euclid, focusing on the expected configuration of its first major data release (DR1). To do this, we 1) simulate a Euclid-like observation and generate mock shear catalogues from multiple realisations of the 3x2pt fields on the sky, and 2) measure the 3x2pt Pseudo-Cl power spectra for a given tomographic configuration and derive the constraints that they place on the standard dark energy equation of state parameters (w0, wa). For a simulation including Gaussian-distributed photometric redshift uncertainty and shape noise under a LambdaCDM cosmology, we find that bins equipopulated with galaxies yield the best constraints on (w0, wa) for an analysis of the full 3x2pt signal, or the angular clustering component only. For the cosmic shear component, the optimum (w0, wa) constraints are achieved by bins equally spaced in fiducial comoving distance. However, the advantage with respect to alternative binning choices is only a few percent in the size of the $1\,\sigma\,$(w0, wa) contour, and we conclude that the cosmic shear is relatively insensitive to the binning methodology. We find that the information gain extracted on (w0, wa) for any 3x2pt component starts to saturate at $\gtrsim$ 7-8 bins. Any marginal gains resulting from a greater number of bins is likely to be limited by additional uncertainties present in a real measurement, and the increasing demand for accuracy of the covariance matrix. Finally, we consider a 5% contamination from catastrophic photometric redshift outliers and find that, if these errors are not mitigated in the analysis, the bias induced in the 3x2pt signal for 10 equipopulated bins results in dark energy constraints that are inconsistent with the fiducial LambdaCDM cosmology at $>5\,\sigma$., Comment: Euclid Consortium paper. 28 pages, 17 figures. For submission to A&A

Anaerobic digestion (AD) offers a sustainable biotechnology to recover resources from carbon-rich wastewater, such as food-processing wastewater. Despite crude wastewater characterisation, the impact of detailed chemical fingerprinting on AD remains underexplored. This study investigated the influence of fermentation-wastewater composition and operational parameters on AD over time to identify critical factors influencing reactor biodiversity and performance. Eighteen reactors were operated under various operational conditions using mycoprotein fermentation wastewater. Detailed chemical analysis fingerprinted the molecules in the fermentation wastewater throughout AD including sugars, sugar alcohols and volatile fatty acids (VFAs). Sequencing revealed distinct microbiome profiles linked to temperature and reactor configuration, with mesophilic conditions supporting a more diverse and densely connected microbiome. Significant elevations in Methanomassiliicoccus were correlated to high butyric acid concentrations and decreased biogas production, further elucidating the role of this newly discovered methanogen. Dissimilarity analysis demonstrated the importance of individual molecules on microbiome diversity, highlighting the need for detailed chemical fingerprinting in AD studies of microbial trends. Machine learning (ML) models predicting reactor performance achieved high accuracy based on operational parameters and microbial taxonomy. Operational parameters had the most substantial influence on chemical oxygen demand removal, whilst Oscillibacter and two Clostridium sp. were highlighted as key factors in biogas production. By integrating detailed chemical and biological fingerprinting with ML models this research presents a novel approach to advance our understanding of AD microbial ecology, offering insights for industrial applications of sustainable waste-to-energy systems., Comment: Original research article, 36 pages, 5198 words, eight figures/tables, one supplementary materials and methods, one supplementary database

Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while proper support from the programming language perspective has been considered secondary or unimportant. Yet, there is mounting evidence that insights from the programming language community may make a difference in the future development of this domain. In this paper, we formulate neural network verification challenges as programming language challenges and suggest possible future solutions., Comment: Accepted at ESOP 2025, European Symposium on Programming Languages

Power Doppler ultrasound is in widespread clinical use for non-invasive vascular imaging but the most common current method - Delay and Sum (DAS) beamforming - suffers from limited resolution and high side-lobes. Here we propose the Sub-Aperture Angular Multiply and Sum (SAMAS) algorithm; it combines the advantages of two recent non-linear beamformers, Frame Multiply and Sum (FMAS) which uses signal temporal coherence and the acoustic sub-aperture (ASAP) algorithm, which uses signal spatial coherence, respectively. Following in vitro experiments to optimise the algorithm, particularly the use of phase information and sub-aperture pairing, it was evaluated in vivo, first in a rabbit kidney and then in human lymph node, using ultrafast ultrasound images obtained with intravenous contrast agents. The SAMAS algorithm improved the CNR and SNR across all tests, on average raising the CNR by 11 dB and the SNR by 18 dB over DAS in vivo. This work demonstrates a promising vascular imaging method that could have widespread clinical utility.

Effective error detection is crucial to prevent task disruption and maintain user trust. Traditional methods often rely on task-specific models or user reporting, which can be inflexible or slow. Recent research suggests social signals, naturally exhibited by users in response to robot errors, can enable more flexible, timely error detection. However, most studies rely on post hoc analysis, leaving their real-time effectiveness uncertain and lacking user-centric evaluation. In this work, we developed a proactive error detection system that combines user behavioral signals (facial action units and speech), user feedback, and error context for automatic error detection. In a study (N = 28), we compared our proactive system to a status quo reactive approach. Results show our system 1) reliably and flexibly detects error, 2) detects errors faster than the reactive approach, and 3) is perceived more favorably by users than the reactive one. We discuss recommendations for enabling robot error awareness in future HRI systems.

The ESA Euclid mission will survey more than 14,000 deg$^2$ of the sky in visible and near-infrared wavelengths, mapping the extra-galactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 deg from the ecliptic, it should allow for the detection of more than about $10^5$ Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1-10 arcsec/h, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on Sourcextractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class., Comment: Accepted for publication on Astronomy and Astrophysics. 15 Pages, 11 Figures

We report the analysis of ~1Ms of XMM-Newton observations of the rapidly accreting active galactic nucleus REJ1034+396. The 0.3-9 keV EPIC-pn spectra are well described by a model consisting of steep continuum emission from the corona accompanied by relativistically-blurred reflection from a highly ionized accretion disk. The source is known to exhibit strong excess soft X-ray emission, which we show is well represented by thermal disk photons Comptonized by a warm plasma spanning the inner accretion flow. Additionally, the EPIC-pn data provide compelling evidence ($\Delta C\sim60$ for 4 additional parameters) for the presence of an ultrafast outflow (UFO) with a line-of-sight velocity $v/c=0.307^{+0.001}_{-0.005}$, and an emission signature consistent with reflection of the corona from modestly ionized, outflowing gas. The simultaneous $0.5-2.5$\,keV RGS spectra show clear absorption lines. Modelling of these data confirms the presence of the UFO and constrains its equivalent hydrogen column density, log $N_\mathrm{H}/$(atom cm$^{-2}$) = $21.7^{+0.1}_{-0.2}$. The RGS data also reveal at least two warm absorber components with a modest outflow velocity ($1680^{+40}_{-50}$ km/s). The measured properties and time evolution of the UFO in REJ1034+396 suggest that it is formed from collisionally ionized plasma, launched from the disk surface and accelerated by radiation pressure. The high terminal velocity and substantial absorbing column density imply that the outflow carries sufficient momentum and energy to transform its environment, being capable of driving out essentially all dust and gas it interacts with along the line of sight, even if the AGN were initially surrounded by a Compton thick absorber., Comment: 10 pages, 6 figures, 2 tables; accepted for publication in ApJ

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

Large Language Models, despite their significant capabilities, are known to fail in surprising and unpredictable ways. Evaluating their true `understanding' of language is particularly challenging due to the extensive web-scale data they are trained on. Therefore, we construct an evaluation to systematically assess natural language understanding (NLU) in LLMs by leveraging Construction Grammar (CxG), which provides insights into the meaning captured by linguistic elements known as constructions (Cxns). CxG is well-suited for this purpose because provides a theoretical basis to construct targeted evaluation sets. These datasets are carefully constructed to include examples which are unlikely to appear in pre-training data, yet intuitive and easy for humans to understand, enabling a more targeted and reliable assessment. Our experiments focus on downstream natural language inference and reasoning tasks by comparing LLMs' understanding of the underlying meanings communicated through 8 unique Cxns with that of humans. The results show that while LLMs demonstrate some knowledge of constructional information, even the latest models including GPT-o1 struggle with abstract meanings conveyed by these Cxns, as demonstrated in cases where test sentences are dissimilar to their pre-training data. We argue that such cases provide a more accurate test of true language understanding, highlighting key limitations in LLMs' semantic capabilities. We make our novel dataset and associated experimental data including prompts and model responses publicly available.

Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane's proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory., Comment: 94 pages

We present the Cosmic Evolution Early Release Science (CEERS) Survey, a 77.2 hour Director's Discretionary Early Release Science Program. CEERS demonstrates, tests, and validates efficient extragalactic surveys using coordinated, overlapping parallel observations with the JWST instrument suite, including NIRCam and MIRI imaging, NIRSpec low (R~100) and medium (R~1000) resolution spectroscopy, and NIRCam slitless grism (R~1500) spectroscopy. CEERS targets the Hubble Space Telescope-observed region of the Extended Groth Strip (EGS) field, supported by a rich set of multiwavelength data. CEERS facilitated immediate community science in both of the extragalactic core JWST science drivers ``First Light" and ``Galaxy Assembly," including: 1) The discovery and characterization of large samples of galaxies at z >~ 10 from ~90 arcmin^2 of NIRCam imaging, constraining their abundance and physical nature; 2) Deep spectra of >1000 galaxies, including dozens of galaxies at 63; and 4) Characterizing galaxy mid-IR emission with MIRI to study dust-obscured star-formation and supermassive black hole growth at z~1-3. As a legacy product for the community, the CEERS team has provided several data releases, accompanied by detailed notes on the data reduction procedures and notebooks to aid in reproducibility. In addition to an overview of the survey and quality of the data, we provide science highlights from the first two years with CEERS data., Comment: 38 pages, 13 figures, 6 tables

We measure for the first time the differential photoproduction cross section $d\sigma/dt$ of the $a_2(1320)$ meson at an average photon beam energy of 8.5~GeV, using data with an integrated luminosity of 104~pb$^{-1}$ collected by the GlueX experiment. We fully reconstruct the $\gamma p \to \eta\pi^0 p$ reaction and perform a partial-wave analysis in the $a_2(1320)$ mass region with amplitudes that incorporate the linear polarization of the beam. This allows us to separate for the first time the contributions of natural- and unnatural-parity exchanges. These measurements provide novel information about the photoproduction mechanism, which is critical for the search for spin-exotic states., Comment: 8 pages, 4 figures plus supplemental material

I present version 5.0 of FRELLED, the FITS Realtime Explorer of Low Latency in Every Dimension. This is a 3D data visualisation package for the popular Blender art software, designed to allow inspection of astronomical volumetric data sets (primarily, but not exclusively, radio wavelength data cubes) in real time using a variety of visualisation techniques. The suite of Python scripts that comprise FRELLED have been almost completely recoded and many new ones added, bringing FRELLED's operating environment from Blender version 2.49 to 2.79. Principle new features include: an enormously simplified installation procedure, a more modular graphical appearance that takes advantage of Blender 2.79's improved interface, much faster loading of FITS data, support for larger data sets, options to show the data as height maps in 2D mode or isosurfaces in 3D mode, utilisation of standard astropy and other Python modules to support a greater range of FITS files (with a particular emphasis on higher-frequency radio data such as from ALMA, the Atacama Large Millimetre Array), and the capability of exporting the data to Blender 2.9+ which supports stereoscopic 3D displays in virtual reality headsets. In addition, in-built help files are accessible from each menu panel, as well as direct links to a complete wiki and set of video tutorials. Finally, the code itself is much more modular, allowing easier maintainability and, over the longer term, a far easier prospect of migrating to more recent versions of Blender., Comment: Accepted for publication in Astronomy & Computing. 23 pages, 7 figures, 2 tables

TOPCAT and STILTS are related packages for desktop analysis of tabular data, presenting GUI and command-line interfaces respectively to much of the same functionality. This paper presents features in TOPCAT that facilitate use of STILTS., Comment: 4 pages, 2 figures; to appear in proceedings of ADASS XXXIV

We explore models where single new exotic states interact with the Standard Model through an asymmetric Standard Model portal with couplings to at least one quark and one lepton. We write down all effective operators up to dimension six where such interactions couple the SM to spin 0 and spin 1/2 particles. We identify the exotic states accessible through the portal and find the interactions couple the SM to new particles with exotic combinations of baryon and lepton number, and particles with unusual SM charge, including states in higher dimensional representations of both SU(3) and SU(2), and states of higher electric charge. We discuss the phenomenology of these interactions including novel particle decays, and we classify some of the collider production modes for exotic states at LHC, LHeC and the muon collider., Comment: 30 pages 10 figures 25 tables

This report summarizes the 5th International Verification of Neural Networks Competition (VNN-COMP 2024), held as a part of the 7th International Symposium on AI Verification (SAIV), that was collocated with the 36th International Conference on Computer-Aided Verification (CAV). VNN-COMP is held annually to facilitate the fair and objective comparison of state-of-the-art neural network verification tools, encourage the standardization of tool interfaces, and bring together the neural network verification community. To this end, standardized formats for networks (ONNX) and specification (VNN-LIB) were defined, tools were evaluated on equal-cost hardware (using an automatic evaluation pipeline based on AWS instances), and tool parameters were chosen by the participants before the final test sets were made public. In the 2024 iteration, 8 teams participated on a diverse set of 12 regular and 8 extended benchmarks. This report summarizes the rules, benchmarks, participating tools, results, and lessons learned from this iteration of this competition., Comment: Report on the results of VNN-COMP 2024. arXiv admin note: substantial text overlap with arXiv:2312.16760, arXiv:2212.10376