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This report explores the dramatic increase in Head Start teacher turnover during the COVID-19 pandemic. Using data from the Head Start Program Information Report (PIR) from 2010 to 2022, the study investigates trends in teacher turnover across all Head Start program types and examines the reasons behind teacher departures. The report finds that teacher turnover surged significantly in both 2020-21 and 2021-22, with the 2021-22 year experiencing a particularly sharp increase exceeding 28% of teachers. Turnover rates varied by program type, with Early Head Start programs exhibiting higher turnover than traditional Head Start programs, and American Indian Alaska Native (AIAN) Early Head Start programs seeing the highest rate at 37.1%. The study reveals that compensation remains the most common reason cited for teachers' departures, both before and during the pandemic. However, COVID-19 related factors also emerged as prominent reasons for departure. This research underscores the urgent need to address the challenges of teacher turnover in the Head Start sector, particularly in the wake of the pandemic. The report advocates for policy initiatives aimed at improving teacher retention through enhanced compensation.

Identifying and removing binary stars from stellar samples is a crucial but complicated task. Regardless of how carefully a sample is selected, some binaries will remain and complicate interpretation of results, especially via flux contamination of survey photometry. One such sample is the data from the Gaia spacecraft, which is collecting photometry and astrometry of more than $10^{9}$ stars. To quantify the impact of binaries on Gaia photometry, we assembled a sample of known binary stars observed with adaptive optics and with accurately measured parameters, which we used to predict Gaia photometry for each stellar component. We compared the predicted photometry to the actual Gaia photometry for each system, and found that the contamination of Gaia photometry because of multiplicity decreases non-linearly from near-complete contamination ($\rho \leq 0''.15$) to no contamination (binary projected separation, or $\rho > 0''.3$). We provide an analytic relation to analytically correct photometric bias in a sample of Gaia stars using the binary separation. This correction is necessary because the Gaia PSF photometry extraction does not fully remove the secondary star flux for binaries with separations with $\rho \lesssim 0''.3$. We also evaluated the utility of various Gaia quality-of-fit metrics for identifying binary stars and found that RUWE remains the best indicator for unresolved binaries, but multi-peak image fraction probes a separation regime not currently accessible to RUWE., Comment: 12 pages, 6 figures, 2 tables. Accepted to AJ

In this paper, we propose a new paradigm for atom interferometry and demonstrate that there exists a universal set of atom optic components for inertial sensing. These components constitute gates with which we carry out quantum operations and represent input-output matterwave transformations between lattice eigenstates. Each gate is associated with a modulation pattern of the position of the optical lattice according to machine-designed protocols. In this methodology, a sensor can be reprogrammed to respond to an evolving set of design priorities without modifying the hardware. We assert that such a gate set is metrologically universal, in analogy to universal gate sets for quantum computing. Experimental confirmation of the designed operation is demonstrated via in situ imaging of the spatial evolution of a Bose-Einstein condensate in an optical lattice, and by measurement of the momentum probabilities following time-of-flight expansion. The representation of several basic quantum sensing circuits is presented for the measurement of inertial forces, rotating reference frames, and gravity gradients., Comment: 16 pages, 19 figures

We introduce KANICE (Kolmogorov-Arnold Networks with Interactive Convolutional Elements), a novel neural architecture that combines Convolutional Neural Networks (CNNs) with Kolmogorov-Arnold Network (KAN) principles. KANICE integrates Interactive Convolutional Blocks (ICBs) and KAN linear layers into a CNN framework. This leverages KANs' universal approximation capabilities and ICBs' adaptive feature learning. KANICE captures complex, non-linear data relationships while enabling dynamic, context-dependent feature extraction based on the Kolmogorov-Arnold representation theorem. We evaluated KANICE on four datasets: MNIST, Fashion-MNIST, EMNIST, and SVHN, comparing it against standard CNNs, CNN-KAN hybrids, and ICB variants. KANICE consistently outperformed baseline models, achieving 99.35% accuracy on MNIST and 90.05% on the SVHN dataset. Furthermore, we introduce KANICE-mini, a compact variant designed for efficiency. A comprehensive ablation study demonstrates that KANICE-mini achieves comparable performance to KANICE with significantly fewer parameters. KANICE-mini reached 90.00% accuracy on SVHN with 2,337,828 parameters, compared to KANICE's 25,432,000. This study highlights the potential of KAN-based architectures in balancing performance and computational efficiency in image classification tasks. Our work contributes to research in adaptive neural networks, integrates mathematical theorems into deep learning architectures, and explores the trade-offs between model complexity and performance, advancing computer vision and pattern recognition. The source code for this paper is publicly accessible through our GitHub repository (https://github.com/m-ferdaus/kanice).

The next generation of smart imaging and vision systems will require compact and tunable optical computing hardware to perform high-speed and low-power image processing. These requirements are driving the development of computing metasurfaces to realize efficient front-end analog optical pre-processors, especially for edge-detection capability. Yet, there is still a lack of reconfigurable or programmable schemes, which may drastically enhance the impact of these devices at the system level. Here, we propose and experimentally demonstrate a reconfigurable flat optical image processor using low-loss phase-change nonlocal metasurfaces. The metasurface is configured to realize different transfer functions in spatial frequency space, when transitioning the phase-change material between its amorphous and crystalline phases. This enables edge detection and bright-field imaging modes on the same device. The metasurface is compatible with a large numerical aperture of ~0.5, making it suitable for high resolution coherent optical imaging microscopy. The concept of phase-change reconfigurable nonlocal metasurfaces may enable emerging applications of artificial intelligence-assisted imaging and vision devices with switchable multitasking., Comment: 20 pages, 5 figures

This study evaluates the productivity improvements achieved using a generative artificial intelligence personal assistant tool (PAT) developed by Trane Technologies. The PAT, based on OpenAI's GPT 3.5 model, was deployed on Microsoft Azure to ensure secure access and protection of intellectual property. To assess the tool's productivity effectiveness, an experiment was conducted comparing the completion times and content quality of four common office tasks: writing an email, summarizing an article, creating instructions for a simple task, and preparing a presentation outline. Sixty-three (63) participants were randomly divided into a test group using the PAT and a control group performing the tasks manually. Results indicated significant productivity enhancements, particularly for tasks involving summarization and instruction creation, with improvements ranging from 3.3% to 69%. The study further analyzed factors such as the age of users, response word counts, and quality of responses, revealing that the PAT users generated more verbose and higher-quality content. An 'LLM-as-a-judge' method employing GPT-4 was used to grade the quality of responses, which effectively distinguished between high and low-quality outputs. The findings underscore the potential of PATs in enhancing workplace productivity and highlight areas for further research and optimization., Comment: 18 pages, 9 figures

Common measures of accuracy used to assess the performance of automatic speech recognition (ASR) systems, as well as human transcribers, conflate multiple sources of error. Stylistic differences, such as verbatim vs non-verbatim, can play a significant role in ASR performance evaluation when differences exist between training and test datasets. The problem is compounded for speech from underrepresented varieties, where the speech to orthography mapping is not as standardized. We categorize the kinds of stylistic differences between 6 transcription versions, 4 human- and 2 ASR-produced, of 10 hours of African American English (AAE) speech. Focusing on verbatim features and AAE morphosyntactic features, we investigate the interactions of these categories with how well transcripts can be compared via word error rate (WER). The results, and overall analysis, help clarify how ASR outputs are a function of the decisions made by the training data's human transcribers., Comment: Published in Interspeech 2024 Proceedings, 5 pages excluding references, 5 figures

Transiting planets in multiple-star systems, especially high-order multiples, make up a small fraction of the known planet population but provide unique opportunities to study the environments in which planets would have formed. Planet-hosting binaries have been shown to have an abundance of systems in which the stellar orbit aligns with the orbit of the transiting planet, which could give insights into the planet formation process in such systems. We investigate here if this trend of alignment extends to planet-hosting triple-star systems. We present long-term astrometric monitoring of a novel sample of triple-star systems that host Kepler transiting planets. We measured orbit arcs in 21 systems, including 12 newly identified triples, from a homogeneous analysis of our Keck adaptive optics data and, for some systems, Gaia astrometry. We examine the orbital alignment within the nine most compact systems ($\lesssim500$ au), testing if either (or both) of the stellar orbits align with the edge-on orbits of their transiting planets. Our statistical sample of triple systems shows a tendency toward alignment, especially when assessing the alignment probability using stellar orbital inclinations computed from full orbital fits, but is formally consistent with isotropic orbits. Two-population tests where half of the stellar orbits are described by a planet-hosting-binary-like moderately aligned distribution give the best match when the other half (non-planet-hosting) has a Kozai-like misaligned distribution. Overall, our results suggest that our sample of triple-star planet-hosting systems are not fully coplanar systems and have at most one plane of alignment., Comment: Accepted to MNRAS

In 2022, the Boston Opportunity Agenda, the Birth to Eight Collaborative and the City of Boston's Office of Early Childhood partnered in the development of this survey of hundreds of early education professionals in the city of Boston, and then expanded its reach to total more than 600 respondents across the state. In it, educators and administrators shared their demographics and educational background, as well as elements of their work experience, wages, and more. Taken together, the data portray a diverse workforce of dedicated professionals who also must manage low wages and long hours in a system that seeks to attract thousands of new workers to replace retiring workers and meet the need for more available early education seats.

Pair-instability supernovae (PISNe) have crucial implications for many astrophysical topics, including the search for very massive stars, the black hole mass spectrum, and galaxy chemical enrichment. To this end, we need to understand where PISNe are across cosmic time, and what are their favourable galactic environments. We present a new determination of the PISN rate as a function of redshift, obtained by combining up-to-date stellar evolution tracks from the PARSEC and FRANEC codes, with an up-to-date semi-empirical determination of the star formation rate and metallicity evolution of star-forming galaxies throughout cosmic history. We find the PISN rate to exhibit a huge dependence on the model assumptions, including the criterion to identify stars unstable to pair production, and the upper limit of the stellar initial mass function. Remarkably, the interplay between the maximum metallicity at which stars explode as PISNe, and the dispersion of the galaxy metallicity distribution, dominates the uncertainties, causing a $\sim$ seven-orders-of-magnitude PISN rate range. Furthermore, we show a comparison with the core-collapse supernova rate, and study the properties of the favourable PISN host galaxies. According to our results, the main contribution to the PISN rate comes from metallicities between $\sim 10^{-3}$ and $10^{-2}$, against the common assumption that views very-low-metallicity, Population III stars as exclusive or dominant PISN progenitors. The strong dependencies we find offer the opportunity to constrain stellar and galaxy evolution models based on possible future (or the lack of) PISN observations., Comment: Accepted for publication on MNRAS, 23 pages, 25 figures, 4 tables

Imbalanced datasets are a significant challenge in real-world scenarios. They lead to models that underperform on underrepresented classes, which is a critical issue in infrastructure inspection. This paper introduces the Enhanced Feature Pyramid Network (E-FPN), a deep learning model for the semantic segmentation of culverts and sewer pipes within imbalanced datasets. The E-FPN incorporates architectural innovations like sparsely connected blocks and depth-wise separable convolutions to improve feature extraction and handle object variations. To address dataset imbalance, the model employs strategies like class decomposition and data augmentation. Experimental results on the culvert-sewer defects dataset and a benchmark aerial semantic segmentation drone dataset show that the E-FPN outperforms state-of-the-art methods, achieving an average Intersection over Union (IoU) improvement of 13.8% and 27.2%, respectively. Additionally, class decomposition and data augmentation together boost the model's performance by approximately 6.9% IoU. The proposed E-FPN presents a promising solution for enhancing object segmentation in challenging, multi-class real-world datasets, with potential applications extending beyond culvert-sewer defect detection.

Speech rate has been shown to vary across social categories such as gender, age, and dialect, while also being conditioned by properties of speech planning. The effect of utterance length, where speech rate is faster and less variable for longer utterances, has also been shown to reduce the role of social factors once it has been accounted for, leaving unclear the relationship between social factors and speech production in conditioning speech rate. Through modelling of speech rate across 13 English speech corpora, it is found that utterance length has the largest effect on speech rate, though this effect itself varies little across corpora and speakers. While age and gender also modulate speech rate, their effects are much smaller in magnitude. These findings suggest utterance length effects may be conditioned by articulatory and perceptual constraints, and that social influences on speech rate should be interpreted in the broader context of how speech rate variation is structured., Comment: Proceedings of Interspeech 2024. 5 pages, 4 figures

We report the discovery of the most eccentric transiting brown dwarf in the brown dwarf desert, TOI02490b. The brown dwarf desert is the lack of brown dwarfs around main sequence stars within $\sim3$~AU and is thought to be caused by differences in formation mechanisms between a star and planet. To date, only $\sim40$ transiting brown dwarfs have been confirmed. \systemt is a $73.6\pm2.4$ \mjupnospace, $1.00\pm0.02$ \rjup brown dwarf orbiting a $1.004_{-0.022}^{+0.031}$ \msunnospace, $1.105_{-0.012}^{+0.012}$ \rsun sun-like star on a 60.33~d orbit with an eccentricity of $0.77989\pm0.00049$. The discovery was detected within \tess sectors 5 (30 minute cadence) and 32 (2 minute and 20 second cadence). It was then confirmed with 31 radial velocity measurements with \feros by the WINE collaboration and photometric observations with the Next Generation Transit Survey. Stellar modelling of the host star estimates an age of $\sim8$~Gyr, which is supported by estimations from kinematics likely placing the object within the thin disc. However, this is not consistent with model brown dwarf isochrones for the system age suggesting an inflated radius. Only one other transiting brown dwarf with an eccentricity higher than 0.6 is currently known in the brown dwarf desert. Demographic studies of brown dwarfs have suggested such high eccentricity is indicative of stellar formation mechanisms., Comment: Accepted for publication in MNRAS, 18 pages, 14 figures

This paper introduces Semantic Haar-Adaptive Refined Pyramid Network (SHARP-Net), a novel architecture for semantic segmentation. SHARP-Net integrates a bottom-up pathway featuring Inception-like blocks with varying filter sizes (3x3$ and 5x5), parallel max-pooling, and additional spatial detection layers. This design captures multi-scale features and fine structural details. Throughout the network, depth-wise separable convolutions are used to reduce complexity. The top-down pathway of SHARP-Net focuses on generating high-resolution features through upsampling and information fusion using $1\times1$ and $3\times3$ depth-wise separable convolutions. We evaluated our model using our developed challenging Culvert-Sewer Defects dataset and the benchmark DeepGlobe Land Cover dataset. Our experimental evaluation demonstrated the base model's (excluding Haar-like features) effectiveness in handling irregular defect shapes, occlusions, and class imbalances. It outperformed state-of-the-art methods, including U-Net, CBAM U-Net, ASCU-Net, FPN, and SegFormer, achieving average improvements of 14.4% and 12.1% on the Culvert-Sewer Defects and DeepGlobe Land Cover datasets, respectively, with IoU scores of 77.2% and 70.6%. Additionally, the training time was reduced. Furthermore, the integration of carefully selected and fine-tuned Haar-like features enhanced the performance of deep learning models by at least 20%. The proposed SHARP-Net, incorporating Haar-like features, achieved an impressive IoU of 94.75%, representing a 22.74% improvement over the base model. These features were also applied to other deep learning models, showing a 35.0% improvement, proving their versatility and effectiveness. SHARP-Net thus provides a powerful and efficient solution for accurate semantic segmentation in challenging real-world scenarios.

We propose diatomic molecules built from gold and carbon-group atoms as promising candidates for optical cycling and precision measurements. We show that this class of molecules (AuX, X = C, Si, Ge, Sn, Pb) features laser-accessible electronic transitions with nearly diagonal Franck-Condon factors. The $^2\Pi_{1/2}$ ground states can be easily polarized in the laboratory frame and have near-zero magnetic moments, valuable features for quantum science and precision measurement applications. The sensitivities of AuX molecules to the electron electric dipole moment (EDM) are found to be favorable, with effective electric fields of 10-30 GV/cm. Together, these features imply that AuX molecules may enable significantly improved searches for time-reversal symmetry violation., Comment: 10 pages, 3 figures

This is the report from the 2023 Particle Physics Project Prioritization Panel (P5) approved by High Energy Physics Advisory Panel (HEPAP) on December 8, 2023. The final version was made public on May 8, 2024 and submitted to DOE SC and NSF MPS., Comment: 2-page spread version. The online version is available at https://www.usparticlephysics.org/2023-p5-report/ and the graphics at https://usparticlephysics.org/media-assets-library

The search for the electromagnetic counterparts to gravitational wave (GW) events has been rapidly gathering pace in recent years thanks to the increasing number and capabilities of both gravitational wave detectors and wide field survey telescopes. Difficulties remain, however, in detecting these counterparts due to their inherent scarcity, faintness and rapidly evolving nature. To find these counterparts, it is important that one optimises the observing strategy for their recovery. This can be difficult due to the large number of potential variables at play. Such follow-up campaigns are also capable of detecting hundreds or potentially thousands of unrelated transients, particularly for GW events with poor localisation. Even if the observations are capable of detecting a counterpart, finding it among the numerous contaminants can prove challenging. Here we present the Gravitational wave Electromagnetic RecovRY code (GERry) to perform detailed analysis and survey-agnostic quantification of observing campaigns attempting to recover electromagnetic counterparts. GERry considers the campaign's spatial, temporal and wavelength coverage, in addition to Galactic extinction and the expected counterpart light curve evolution from the GW 3D localisation volume. It returns quantified statistics that can be used to: determine the probability of having detected the counterpart, identify the most promising sources, and assess and refine strategy. Here we demonstrate the code to look at the performance and parameter space probed by current and upcoming wide-field surveys such as GOTO & VRO., Comment: 19 pages, 11 figures, submitted to SPIE Astronomical Telescopes + Instrumentation 2024

The Gravitational-wave Optical Transient Observer (GOTO) is a project dedicated to identifying optical counter-parts to gravitational-wave detections using a network of dedicated, wide-field telescopes. After almost a decade of design, construction, and commissioning work, the GOTO network is now fully operational with two antipodal sites: La Palma in the Canary Islands and Siding Spring in Australia. Both sites host two independent robotic mounts, each with a field-of-view of 44 square degrees formed by an array of eight 40 cm telescopes, resulting in an instantaneous 88 square degree field-of-view per site. All four telescopes operate as a single integrated network, with the ultimate aim of surveying the entire sky every 2-3 days and allowing near-24-hour response to transient events within a minute of their detection. In the modern era of transient astronomy, automated telescopes like GOTO form a vital link between multi-messenger discovery facilities and in-depth follow-up by larger telescopes. GOTO is already producing a wide range of scientific results, assisted by an efficient discovery pipeline and a successful citizen science project: Kilonova Seekers., Comment: 8 pages, 5 figures, submitted to SPIE Astronomical Telescopes + Instrumentation 2024

Grids of stellar evolution models with rotation using the Geneva stellar evolution code (Genec) have been published for a wide range of metallicities. We introduce the last remaining grid of Genec models, with a metallicity of $Z=10^{-5}$. We study the impact of this extremely metal-poor initial composition on various aspects of stellar evolution, and compare it to the results from previous grids at other metallicities. We provide electronic tables that can be used to interpolate between stellar evolution tracks and for population synthesis. Using the same physics as in the previous papers of this series, we computed a grid of stellar evolution models with Genec spanning masses between 1.7 and 500 $M_\odot$, with and without rotation, at a metallicity of $Z=10^{-5}$. Due to the extremely low metallicity of the models, mass-loss processes are negligible for all except the most massive stars. For most properties (such as evolutionary tracks in the Hertzsprung-Russell diagram, lifetimes, and final fates), the present models fit neatly between those previously computed at surrounding metallicities. However, specific to this metallicity is the very large production of primary nitrogen in moderately rotating stars, which is linked to the interplay between the hydrogen- and helium-burning regions. The stars in the present grid are interesting candidates as sources of nitrogen-enrichment in the early Universe. Indeed, they may have formed very early on from material previously enriched by the massive short-lived Population III stars, and as such constitute a very important piece in the puzzle that is the history of the Universe., Comment: Accepted in A&A. 20 pages, 14 figures, 3 tables

We experimentally demonstrate two multidimensional atom interferometers capable of measuring both the magnitude and direction of applied inertial forces. These interferometers do not rely on the ubiquitous light-pulses of traditional atom sensors, but are instead built from an innovative design that operates entirely within the Bloch bands of an optical lattice formed by interfering laser beams. Through time-dependent control of the position of the lattice in three-dimensional space, we realize simultaneous Bloch oscillations in two dimensions, and a vector atomic Michelson interferometer. Fits to the observed Bloch oscillations demonstrate the measurement of an applied acceleration of $2g$ along two axes, where $g$ is the average gravitational acceleration at the Earth's surface. For the Michelson interferometer, we perform Bayesian inferencing from a 49-channel output by repeating experiments for selected examples of two-axis accelerations. We demonstrate the resulting accuracy and sensitivity for vector parameter estimation. Our acceleration can be measured from a single experimental run and does not require repeated shots to construct a fringe. We find the performance of our device to be near the quantum limit for the interferometer size and quantum detection efficiency of the atoms. We discuss the reconfigurability of the vector accelerometer and the pathway toward further sensitivity.

Small planets ($R_{p} \leq 4 R_{\oplus}$) are divided into rocky super-Earths and gaseous sub-Neptunes separated by a radius gap, but the mechanisms that produce these distinct planet populations remain unclear. Binary stars are the only main-sequence systems with an observable record of the protoplanetary disk lifetime and mass reservoir, and the demographics of planets in binaries may provide insights into planet formation and evolution. To investigate the radius distribution of planets in binary star systems, we observed 207 binary systems hosting 283 confirmed and candidate transiting planets detected by the Kepler mission, then recharacterized the planets while accounting for the observational biases introduced by the secondary star. We found that the population of planets in close binaries ($\rho \leq 100$ au) is significantly different from the planet population in wider binaries ($\rho > 300$ au) or single stars. In contrast to planets around single stars, planets in close binaries appear to have a unimodal radius distribution with a peak near the expected super-Earth peak of $R_{p} \sim 1.3 R_{\oplus}$ and a suppressed population of sub-Neptunes. We conclude that we are observing the direct impact of a reduced disk lifetime, smaller mass reservoir, and possible altered distribution of solids reducing the sub-Neptune formation efficiency. Our results demonstrate the power of binary stars as a laboratory for exploring planet formation and as a controlled experiment of the impact of varied initial conditions on mature planet populations., Comment: 19 pages, 9 figures, 6 tables. Accepted to AJ. Full tables available upon request to the first author prior to publication

The rapid progress in Large Language Models (LLMs) could transform many fields, but their fast development creates significant challenges for oversight, ethical creation, and building user trust. This comprehensive review looks at key trust issues in LLMs, such as unintended harms, lack of transparency, vulnerability to attacks, alignment with human values, and environmental impact. Many obstacles can undermine user trust, including societal biases, opaque decision-making, potential for misuse, and the challenges of rapidly evolving technology. Addressing these trust gaps is critical as LLMs become more common in sensitive areas like finance, healthcare, education, and policy. To tackle these issues, we suggest combining ethical oversight, industry accountability, regulation, and public involvement. AI development norms should be reshaped, incentives aligned, and ethics integrated throughout the machine learning process, which requires close collaboration across technology, ethics, law, policy, and other fields. Our review contributes a robust framework to assess trust in LLMs and analyzes the complex trust dynamics in depth. We provide contextualized guidelines and standards for responsibly developing and deploying these powerful AI systems. This review identifies key limitations and challenges in creating trustworthy AI. By addressing these issues, we aim to build a transparent, accountable AI ecosystem that benefits society while minimizing risks. Our findings provide valuable guidance for researchers, policymakers, and industry leaders striving to establish trust in LLMs and ensure they are used responsibly across various applications for the good of society., Comment: Under review at Proceedings of the IEEE

This report presents the details of a year-long study conducted by Research for Action of the impact and implementation of the Children's Literacy Initiative (CLI) Pre-K Intervention. Thirty-five district-operated and community-based Pre-K programs from Broward County Public Schools and the Early Learning Coalition of Broward County were enrolled and randomly assigned to programs with the intervention and those operating under "business as usual" conditions. CLI hypothesized that state and local decisionmakers need a comprehensive Pre-K curriculum based in equal parts on the science of child development and the realities of the current early childhood workforce. CLI's intervention targeted low- and middle-income children enrolled in state-funded universal public Pre-K settings, investing in resources for children and the programs that serve them who live in historically under-resourced communities. The evaluation was guided by three overarching aims: (1) Examine the impact of CLI's intervention on key skills that prepare children for success in Kindergarten ("Impact Study"); (2) Describe thresholds for fidelity of the intervention and document the extent to which CLI met the thresholds in the study ("Implementation Study"); and (3) Evaluate the implementation of CLI's intervention in classrooms serving students with disabilities or development delays ("Case Study"). RFA found that implementing CLI's program was challenging, especially when it came to providing enough training for teachers and site leader professional learning. Because of these challenges, the study didn't find any evidence that CLI's program made a difference in how well students understood phonological awareness or numeracy (sounds or numbers). Overall, kids in both groups ended the year with skills that were expected for their age.

The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography systems, models built using data from one system do not generalize well to other systems. Though federated learning (FL) has emerged as a way to improve the generalizability of AI without the need to share data, the best way to preserve features from all training data during FL is an active area of research. To explore FL methodology, the breast density classification FL challenge was hosted in partnership with the American College of Radiology, Harvard Medical School's Mass General Brigham, University of Colorado, NVIDIA, and the National Institutes of Health National Cancer Institute. Challenge participants were able to submit docker containers capable of implementing FL on three simulated medical facilities, each containing a unique large mammography dataset. The breast density FL challenge ran from June 15 to September 5, 2022, attracting seven finalists from around the world. The winning FL submission reached a linear kappa score of 0.653 on the challenge test data and 0.413 on an external testing dataset, scoring comparably to a model trained on the same data in a central location., Comment: 16 pages, 9 figures

The TOI-178 system consists of a nearby late K-dwarf transited by six planets in the super-Earth to mini-Neptune regime, with radii ranging from 1.2 to 2.9 earth radius and orbital periods between 1.9 and 20.7 days. All planets but the innermost one form a chain of Laplace resonances. The fine-tuning and fragility of such orbital configurations ensure that no significant scattering or collision event has taken place since the formation and migration of the planets in the protoplanetary disc, hence providing important anchors for planet formation models. We aim to improve the characterisation of the architecture of this key system, and in particular the masses and radii of its planets. In addition, since this system is one of the few resonant chains that can be characterised by both photometry and radial velocities, we aim to use it as a test bench for the robustness of the planetary mass determination with each technique. We perform a global analysis of all available photometry and radial velocity. We also try different sets of priors on the masses and eccentricity, as well as different stellar activity models, to study their effects on the masses estimated by each method. We show how stellar activity is preventing us from obtaining a robust mass estimation for the three outer planets using radial velocity data alone. We also show that our joint photo-dynamical and radial velocity analysis resulted in a robust mass determination for planets c to g, with precision of 12% for the mass of planet c, and better than 10% for planets d to g. The new precisions on the radii range from 2 to 3%. The understanding of this synergy between photometric and radial velocity measurements will be valuable during the PLATO mission. We also show that TOI-178 is indeed currently locked in the resonant configuration, librating around an equilibrium of the chain.

Discovering transiting exoplanets with relatively long orbital periods ($>$10 days) is crucial to facilitate the study of cool exoplanet atmospheres ($T_{\rm eq} < 700 K$) and to understand exoplanet formation and inward migration further out than typical transiting exoplanets. In order to discover these longer period transiting exoplanets, long-term photometric and radial velocity campaigns are required. We report the discovery of TOI-2447 b ($=$ NGTS-29b), a Saturn-mass transiting exoplanet orbiting a bright (T=10.0) Solar-type star (T$_{\rm eff}$=5730 K). TOI-2447 b was identified as a transiting exoplanet candidate from a single transit event of 1.3% depth and 7.29 h duration in $TESS$ Sector 31 and a prior transit event from 2017 in NGTS data. Four further transit events were observed with NGTS photometry which revealed an orbital period of P=69.34 days. The transit events establish a radius for TOI-2447 b of $0.865 \pm 0.010\rm R_{\rm J}$, while radial velocity measurements give a mass of $0.386 \pm 0.025 \rm M_{\rm J}$. The equilibrium temperature of the planet is $414$ K, making it much cooler than the majority of $TESS$ planet discoveries. We also detect a transit signal in NGTS data not caused by TOI-2447 b, along with transit timing variations and evidence for a $\sim$150 day signal in radial velocity measurements. It is likely that the system hosts additional planets, but further photometry and radial velocity campaigns will be needed to determine their parameters with confidence. TOI-2447 b/NGTS-29b joins a small but growing population of cool giants that will provide crucial insights into giant planet composition and formation mechanisms., Comment: 16 pages, 12 figures. Accepted for publication in MNRAS

Young stars form in associations, meaning that young stellar associations provide an ideal environment to measure the age of a nominally coeval population. Isochrone fitting, which is the typical method for measuring the age of a coeval population, can be impacted by observational biases that obscure the physical properties of a population. One feature in isochrone fits of star-forming regions is an apparent mass-dependent age gradient, where lower-mass stars appear systematically younger than higher-mass stars. Starspots and stellar multiplicity are proposed mechanisms for producing the mass-dependent age gradient, but the relative importance of starspots versus multiplicity remains unclear. We performed a synthetic red-optical low-resolution spectroscopic survey of a simulated analog to a 10 Myr stellar association including mass-dependent multiplicity statistics and age-dependent starspot coverage fractions. We found that undetected starspots alone do not produce an apparent mass-dependent age gradient, but instead uniformly reduce the average measured age of the population. We also found that binaries continue to produce an apparent mass-dependent age gradient, and introduce more scatter in the age measurement than spots, but are easily removed from the population as long as there are good distance measurements to each target. We conclude that it is crucial to incorporate treatments of both starspots and undetected stellar multiplicity into isochrone fits of young stellar associations to attain reliable ages., Comment: 12 pages and 8 figures; accepted to ApJ

Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Building upon Gemini's multimodal models, we develop several models within the new Med-Gemini family that inherit core capabilities of Gemini and are optimized for medical use via fine-tuning with 2D and 3D radiology, histopathology, ophthalmology, dermatology and genomic data. Med-Gemini-2D sets a new standard for AI-based chest X-ray (CXR) report generation based on expert evaluation, exceeding previous best results across two separate datasets by an absolute margin of 1% and 12%, where 57% and 96% of AI reports on normal cases, and 43% and 65% on abnormal cases, are evaluated as "equivalent or better" than the original radiologists' reports. We demonstrate the first ever large multimodal model-based report generation for 3D computed tomography (CT) volumes using Med-Gemini-3D, with 53% of AI reports considered clinically acceptable, although additional research is needed to meet expert radiologist reporting quality. Beyond report generation, Med-Gemini-2D surpasses the previous best performance in CXR visual question answering (VQA) and performs well in CXR classification and radiology VQA, exceeding SoTA or baselines on 17 of 20 tasks. In histopathology, ophthalmology, and dermatology image classification, Med-Gemini-2D surpasses baselines across 18 out of 20 tasks and approaches task-specific model performance. Beyond imaging, Med-Gemini-Polygenic outperforms the standard linear polygenic risk score-based approach for disease risk prediction and generalizes to genetically correlated diseases for which it has never been trained. Although further development and evaluation are necessary in the safety-critical medical domain, our results highlight the potential of Med-Gemini across a wide range of medical tasks.

We present the results from the first two years of the Planet Hunters NGTS citizen science project, which searches for transiting planet candidates in data from the Next Generation Transit Survey (NGTS) by enlisting the help of members of the general public. Over 8,000 registered volunteers reviewed 138,198 light curves from the NGTS Public Data Releases 1 and 2. We utilize a user weighting scheme to combine the classifications of multiple users to identify the most promising planet candidates not initially discovered by the NGTS team. We highlight the five most interesting planet candidates detected through this search, which are all candidate short-period giant planets. This includes the TIC-165227846 system that, if confirmed, would be the lowest-mass star to host a close-in giant planet. We assess the detection efficiency of the project by determining the number of confirmed planets from the NASA Exoplanet Archive and TESS Objects of Interest (TOIs) successfully recovered by this search and find that 74% of confirmed planets and 63% of TOIs detected by NGTS are recovered by the Planet Hunters NGTS project. The identification of new planet candidates shows that the citizen science approach can provide a complementary method to the detection of exoplanets with ground-based surveys such as NGTS., Comment: 42 pages, 20 figures, 17 tables. To be published in AJ

Understanding bidding behavior in multi-unit auctions remains an ongoing challenge for researchers. Despite their widespread use, theoretical insights into the bidding behavior, revenue ranking, and efficiency of commonly used multi-unit auctions are limited. This paper utilizes artificial intelligence, specifically reinforcement learning, as a model free learning approach to simulate bidding in three prominent multi-unit auctions employed in practice. We introduce six algorithms that are suitable for learning and bidding in multi-unit auctions and compare them using an illustrative example. This paper underscores the significance of using artificial intelligence in auction design, particularly in enhancing the design of multi-unit auctions.

Long-period transiting exoplanets bridge the gap between the bulk of transit- and Doppler-based exoplanet discoveries, providing key insights into the formation and evolution of planetary systems. The wider separation between these planets and their host stars results in the exoplanets typically experiencing less radiation from their host stars; hence, they should maintain more of their original atmospheres, which can be probed during transit via transmission spectroscopy. Although the known population of long-period transiting exoplanets is relatively sparse, surveys performed by the Transiting Exoplanet Survey Satellite (TESS) and the Next Generation Transit Survey (NGTS) are now discovering new exoplanets to fill in this crucial region of the exoplanetary parameter space. This study presents the detection and characterisation of NGTS-30 b/TOI-4862 b, a new long-period transiting exoplanet detected by following up on a single-transit candidate found in the TESS mission. Through monitoring using a combination of photometric instruments (TESS, NGTS, and EulerCam) and spectroscopic instruments (CORALIE, FEROS, HARPS, and PFS), NGTS-30 b/TOI-4862 b was found to be a long-period (P = 98.29838 day) Jupiter-sized (0.928 RJ; 0.960 MJ) planet transiting a 1.1 Gyr old G-type star. With a moderate eccentricity of 0.294, its equilibrium temperature could be expected to vary from 274 K to 500 K over the course of its orbit. Through interior modelling, NGTS-30 b/TOI-4862 b was found to have a heavy element mass fraction of 0.23 and a heavy element enrichment (Zp/Z_star) of 20, making it metal-enriched compared to its host star. NGTS-30 b/TOI-4862 b is one of the youngest well-characterised long-period exoplanets found to date and will therefore be important in the quest to understanding the formation and evolution of exoplanets across the full range of orbital separations and ages., Comment: 18 pages, 14 figures, accepted for publication in A&A

We present the semi-analytical light curve modelling of 13 supernovae associated with gamma-ray bursts (GRB-SNe) along with two relativistic broad-lined (Ic-BL) SNe without GRBs association (SNe 2009bb and 2012ap), considering millisecond magnetars as central-engine-based power sources for these events. The bolometric light curves of all 15 SNe in our sample are well-regenerated utilising a $\chi^2-$minimisation code, $\texttt{MINIM}$, and numerous parameters are constrained. The median values of ejecta mass ($M_{\textrm{ej}}$), magnetar's initial spin period ($P_\textrm{i}$) and magnetic field ($B$) for GRB-SNe are determined to be $\approx$ 5.2 M$_\odot$, 20.5 ms and 20.1 $\times$ 10$^{14}$ G, respectively. We leverage machine learning (ML) algorithms to comprehensively compare the 3-dimensional parameter space encompassing $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ for GRB-SNe determined herein to those of H-deficient superluminous SNe (SLSNe-I), fast blue optical transients (FBOTs), long GRBs (LGRBs), and short GRBs (SGRBs) obtained from the literature. The application of unsupervised ML clustering algorithms on the parameters $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ for GRB-SNe, SLSNe-I, and FBOTs yields a classification accuracy of $\sim$95%. Extending these methods to classify GRB-SNe, SLSNe-I, LGRBs, and SGRBs based on $P_\textrm{i}$ and $B$ values results in an accuracy of $\sim$84%. Our investigations show that GRB-SNe and relativistic Ic-BL SNe presented in this study occupy different parameter spaces for $M_{\textrm{ej}}$, $P_\textrm{i}$, and $B$ than those of SLSNe-I, FBOTs, LGRBs and SGRBs. This indicates that magnetars with different $P_\textrm{i}$ and $B$ can give birth to distinct types of transients., Comment: 13 pages, 7 figures, and 3 tables (including appendix). Accepted for publication in MNRAS

Few laboratory studies have investigated the vapor pressures of the volatiles that may be present as ices in the outer solar system; even fewer studies have investigated these species at the temperatures and pressures suitable to the surfaces of icy bodies in the Saturnian and Uranian systems ($\lt$100 K, $\lt10^{-9}$ bar). This study adds to the work of Grundy et al. (2024) in extending the known equilibrium vapor pressures of outer solar system ices through laboratory investigations at very low temperatures. Our experiments with ammonia and oxygen ices provide new thermodynamic models for these species' respective enthalpies of sublimation. We find that ammonia ice, and to a lesser degree oxygen ice, are stable at higher temperatures than extrapolations in previous literature have predicted. Our results show that these ices should be retained over longer periods of time than previous extrapolations would predict, and a greater amount of these solids is required to support observation in exospheres of airless bodies in the outer solar system., Comment: 29 pages, 9 figures, to be published in Planetary and Space Science

We numerically simulate the motion of a black hole as it plunges radially through an ultralight dark matter soliton. We investigate the timescale in which dynamical friction reduces the kinetic energy of the black hole to a minimum, and consider the sensitivity of this timescale to changes in the ULDM particle mass, the total soliton mass, and the mass of the black hole. We contrast our numerical results with a semi-analytic treatment of dynamical friction, and find that the latter is poorly suited to this scenario. In particular, we find that the back-reaction of the soliton to the presence of the black hole is significant, resulting in oscillations in the coefficient of dynamical friction which cannot be described in the simple semi-analytical framework. Furthermore, we observe a late-time reheating effect, in which a significant amount of kinetic energy is transferred back to the black hole after an initial damping phase. This complicates the discussion of ULDM dynamical friction on the scales relevant to the final parsec problem., Comment: 15 pages