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The detailed guide's purpose is to assist educators and community leaders in designing and implementing educational programs to serve student and community needs, and to identify the goals and elements of cooperative vocational education. One chapter describes the necessary characteristics of the teacher-coordinator in such programs, and the advantages of cooperative vocational education to the community and to the students. Two other chapters suggest methods for determining employers' and students' needs for cooperative vocational education and suggest plans for meeting these needs. Three chapters deal with implementing plans for: public relations (including a suggested eight point plan and the use of media); instruction in the school (including five teaching methods and the use of youth organizations); and community laboratories (including criteria for selecting, establishing, and evaluating training stations, and guidelines for complying with appropriate laws). Another chapter analyzes essential elements of the cooperative program including staffing; facilities, equipment, and materials; and program development. A final chapter suggests ways of improving cooperative vocational education in its administrative structure, professional development of teacher-coordinators, instructional materials, and program evaluation. A 70-page appendix displays forms appropriate to the planning, implementation, and evaluation of programs. (JR)

California's K-12 funding and instructional policies for English learners (ELs) have changed significantly over the past 2 decades, including new requirements for instructional materials specific to ELs statewide and a new school funding system that funds ELs at a higher rate. These major policy shifts held the potential to change student learning outcome patterns for ELs. This brief summarizes those policy changes and, as a first step in identifying their impact, describes changes over time in the development of academic skills and English proficiency among ELs in California. We find that English learners' academic achievement by 3rd grade has improved over time, shrinking the achievement gaps between K-cohort ELs and other students in English language arts (ELA) and math. We also find that more-recent cohorts of kindergarten ELs are reaching English proficiency on the California English Language Development Test (CELDT) in earlier grades than previous cohorts did. For the less recent cohorts who had reached Grade 5 by 2018-19, we find almost no change in the overall share who were proficient in English by the end of elementary school. We also find only half of kindergarten ELs were reclassified as English proficient by the end of elementary school in 2018-19.

Open educational resources (OER) are teaching, learning, or research resources that are offered freely to users in at least one form and that either reside in the public domain or have been released under an open copyright license that allows for its free use, reuse, modification, and sharing with attribution. Course marking (also called attributes, designations, tags, flags, labels) are specific, searchable attributes or designations that are applied to courses, allowing students to quickly identify important information to aid in their decision making and allow them to efficiently plan their academic careers. In 2022, the report, "Toward Convergence: Creating Clarity to Drive More Consistency in Understanding the Benefits and Costs of OER," introduced a set of principles and frameworks that provide guidance for states, systems, and institutions wanting to better understand the benefits of open educational resources (OER). MHEC led the national effort to produce the report, which details recommendations for consistently estimating the cost savings realized by students when a course uses OER compared to traditional course material. Realizing such analyses are not possible without accurate data on course materials, MHEC then led a national effort to create this report to highlight five steps critical for the development of an effective course marking process, providing committed stakeholders with a roadmap and set of recommendations to improve consistency and reliability for marking courses in college registration materials, so students know the costs and nature of such materials at the time they choose their classes. Consistency of course marking efforts across the United States contributes to the ability to aggregate data from many institutions and conduct studies of how OER saves students money and contributes to enhanced student outcomes.

Using data from the Quarterly Workforce Indicators, this brief explores changes in the Los Angeles County labor market and in the working-age population as a plausible explanation for some of the enrollment decline at the county's community college campuses.

Students, families, and communities across Chicago are affected by gun violence, but the levels and experiences differ greatly by location and by the racial composition of communities. In Chicago, recent rates of violence rose sharply during the COVID-19 pandemic, and then declined to pre-pandemic levels in 2022. Still, there were more than 4,000 gun-related injuries reported to the Chicago Police Department in 2020 and in 2021, and homicides in the city rose in tandem. While overall rates of violence have fallen from peaks in the late 1990s in predominantly White and Latinx communities, rates of violence in Chicago's predominantly Black communities have exceeded 1990s levels in recent years. Of the 725 homicides reported in Chicago in 2022, 541 victims were Black, more than 18 times as many as were White. Proximity to violence and homicide remain profoundly racialized in Chicago. This mixed-methods study explores four interconnected research questions, specifically examining the particular role schools may play in the lives of students living in proximity to violence in Chicago: (1) What is the extent, distribution, and impact of living in close geographical proximity to violence on CPS students' performance in schools? (2) To what extent is there evidence that CPS schools can insulate or protect students from the negative consequences on academic and behavioral outcomes of living in close proximity to violence, so as to support students' health and wellness? (3) What elements of school climate and organization are characteristic of schools that appear to protect students against the negative impacts of proximity to violence on academic and behavioral outcomes? and (4) How do adults working in schools that insulate students from the impact of living in close proximity to violence understand and describe their work?

National context: Schools across the United States have long grappled with the role and impact of school-based police officers, often referred to as school resource officers (SROs). Proponents for school-based policing believe that SROs contribute to school safety by preventing or addressing crime and violence in schools. Opponents of SROs in schools argue that the presence of SROs criminalizes students and increases the likelihood of school-based arrest, particularly for students of color. Policies around SROs vary in districts across the country. Chicago context: In the wake of George Floyd's murder in 2020, the Chicago Board of Education (CBOE) asked the district to develop a plan to phase-out the SRO program, which assigned two SROs to most Chicago Public Schools (CPS) high schools. In February 2024, the CBOE voted to remove all remaining SROs from schools starting in 2024-25. In May 2024, CPS proposed a Whole School Safety Policy that did not include SROs and focused on supports for physical safety, emotional safety, and relational trust in schools. The research: This brief examines what happened when Chicago Public Schools (CPS) began the process of removing School Resource Officers (SROs) from its high schools during the 2020-21 school year. These findings can inform conversations in Chicago, and across the country, about SROs and whole school safety practices and policies--while recognizing that questions about the presence of police and the experience of safety in schools are complex and reflect differences in lived experiences and perspectives across policymakers, practitioners, young people, families, and communities. The findings are part of a larger, ongoing study by researchers from the UChicago Consortium; University of Illinois, Urbana-Champaign; and Lurie Children's Hospital's Center for Childhood Resilience. [This research brief received additional support from the Pritzker-Pucker Family Foundation and the Consortium Investor Council.]

Appropriately identifying children with disabilities--in ways that are timely, comprehensive, and accurate--is critical for ensuring that learners receive the supports they need to meet early milestones and succeed in school. In turn, the Individuals with Disabilities Education Act (IDEA) charges states and school districts with: (1) finding all children, birth through age 21, suspected of having a disability; (2) evaluating them to determine if they are eligible for IDEA services; and (3) measuring and addressing racial or ethnic disparities in who is identified. Since IDEA's reauthorization in 2004, there is greater access to data and more sophisticated approaches to screen for and detect certain disabilities, an increasingly diverse child population, and new regulations on how to measure disparities in identification. This report examines how state and district practices during the 2019-2020 school year aligned with IDEA's goals of appropriate identification.

Metallicities of both gas and stars decline toward large radii in spiral galaxies, a trend known as the radial metallicity gradient. We quantify the evolution of the metallicity gradient in the Milky Way as traced by APOGEE red giants with age estimates from machine learning algorithms. Stars up to ages of $\sim$9 Gyr follow a similar relation between metallicity and Galactocentric radius. This constancy challenges current models of Galactic chemical evolution, which typically predict lower metallicities for older stellar populations. Our results favor an equilibrium scenario, in which the gas-phase gradient reaches a nearly constant normalization early in the disk lifetime. Using a fiducial choice of parameters, we demonstrate that one possible origin of this behavior is an outflow that more readily ejects gas from the interstellar medium with increasing Galactocentric radius. A direct effect of the outflow is that baryons do not remain in the interstellar medium for long, which causes the ratio of star formation to accretion, $\dot{\Sigma}_\star / \dot{\Sigma}_\text{in}$, to quickly become constant. This ratio is closely related to the local equilibrium metallicity, since its numerator and denominator set the rates of metal production by stars and hydrogen gained through accretion, respectively. Building in a merger event results in a perturbation that evolves back toward the equilibrium state on $\sim$Gyr timescales. Under the equilibrium scenario, the radial metallicity gradient is not a consequence of the inside-out growth of the disk but instead reflects a trend of declining $\dot{\Sigma}_\star / \dot{\Sigma}_\text{in}$ with increasing Galactocentric radius., Comment: submitted to ApJ, comments welcome

We develop a systems approach based on an energy-landscape concept to differentiate interactions involving redox activities and conformational changes of proteins and nucleic acids interactions in multi-layered protein-DNA regulatory networks under light disturbance. Our approach is a data-driven modeling workflow using a physics-informed machine learning algorithm to train a non-linear mathematical model for interpreting gene expression dynamics and to lead discovery for protein regulators using redox proteome analysis. We distinguish light-responsive elements within central carbon metabolism pathways from independent variables like circadian time using the publicly available transcriptome datasets of Synechococcus elongatus over diel cycles responding to light perturbations. Our approach provides interpretable de novo models for elucidating events of reactions in complex regulatory pathways in response to stressful disturbance from the environment. We discovered protein regulators in response to light disturbance in the proteome analysis involving shifts in protein abundance as well as cysteine redox states under constant illumination and after two hours of darkness. We discovered significant shifts in cysteine redox states in regulatory proteins such as transcription sigma factors and metabolic enzymes in the oxidative pentose phosphate pathway and the Calvin-Benson cycle, while the changes in their protein abundance were minimal. These results indicate that regulatory dynamics in reductant generation link photo-induced electron transport pathways and redox metabolic pathways with circadian rhythms through fast redox-induced conformational changes or slow expression regulations across networks.

Youth Participatory Action Research (YPAR) is traditionally valued for its developmental benefits for youth, such as enhancing leadership and critical thinking skills. However, this brief evidences that YPAR's potential extends significantly beyond individual growth, serving as a powerful mechanism for organizational development and academic field-building. We explore how YPAR facilitates local insights into organizational practices from a youth perspective and contributes uniquely to the broader academic discourse, effectively bridging the research-practice gap.

The dissociation of quarkonium states with different binding energies produced in heavy-ion collisions is a powerful probe for investigating the formation and properties of the quark-gluon plasma. The ratio of production cross-sections of $\psi(2S)$ and $J/\psi$ mesons times the ratio of their branching fractions into the dimuon final state is measured as a function of centrality using data collected by the LHCb detector in PbPb collisions at $\sqrt{s_{\text{NN}}}$ = 5.02 TeV. The measured ratio shows no dependence on the collision centrality, and is compared to the latest theory predictions and to the recent measurements in literature., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-041.html (LHCb public pages)

The He II reionization epoch is expected to take place at $z\sim3-5$. In this stage, the helium and metals in the inter-galactic medium (IGM) are further ionized with additional contributions from harder non-stellar sources, and some large-scale gravitationally bound systems approach virialization. The "Probing the He II re-Ionization ERa via Absorbing C IV Historical Yield (HIERACHY)" program utilizes high- and medium-resolution spectra of bright background quasars at $z\approx3.9-5.2$ to investigate Ly$\alpha$, C IV, and other metal absorption lines during this epoch. Additionally, we employ narrow-band imaging to search for Ly$\alpha$ emitters associated with C IV absorbers, alongside multi-wavelength observations to identify and study particularly intriguing cases. In this paper, we present the design of the HIERACHY program, its current status, major scientific goals, and examples of initial data products from completed Magellan/MIKE, MagE spectroscopy, and MDM imaging observations. We also provide a brief outlook on future multi-wavelength observations that may significantly impact the related science., Comment: 25 pages, 10 figures, 2 tables, accepted for publication by ApJ

Most AI tools adopted by governments are not developed internally, but instead are acquired from third-party vendors in a process called public procurement. While scholars and regulatory proposals have recently turned towards procurement as a site of intervention to encourage responsible AI governance practices, little is known about the practices and needs of city employees in charge of AI procurement. In this paper, we present findings from semi-structured interviews with 18 city employees across 7 US cities. We find that AI acquired by cities often does not go through a conventional public procurement process, posing challenges to oversight and governance. We identify five key types of challenges to leveraging procurement for responsible AI that city employees face when interacting with colleagues, AI vendors, and members of the public. We conclude by discussing recommendations and implications for governments, researchers, and policymakers., Comment: Preprint, under revision

This paper summarises the intersection of Web3 and AI technologies, synergies between these technologies, and gaps that we suggest exist in the conception of the possible integrations of these technologies. The summary is informed by a comprehensive literature review of current academic and industry papers, analyst reports, and Ethereum research community blogposts. We focus our contribution on the perceived gaps and detail some novel approaches that would benefit the blockchain/Web3 ecosystem. We believe that the overview presented in this paper will help guide researchers interested in the intersection of Web3 and AI technologies., Comment: 20 pages, 6 figures

An amplitude analysis of the $D_{s1}(2460)^+\to D_{s}^{+}\pi^{+}\pi^{-}$ transition is performed simultaneously in $B^{0}\to D^{-}D_{s}^{+}\pi^{+}\pi^{-}$, $B^{+}\to{\bar{D}}^{0} D_{s}^{+}\pi^{+}\pi^{-}$, and $B^{0}\to D^{*-}D_{s}^{+}\pi^{+}\pi^{-}$ decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at centre-of-mass energies of $\sqrt{s}=7,8,$ and $13\,$TeV, corresponding to a total integrated luminosity of $9\,\rm{fb}^{-1}$. A clear double-peak structure is observed in the $m(\pi^{+}\pi^{-})$ spectrum of the $D_{s1}(2460)^{+}\to D_{s}^{+}\pi^{+}\pi^{-}$ decay. The data can be described either with a model including $f_0(500)$, $f_0(980)$ and $f_2(1270)$ resonances, in which the contributions of $f_0(980)$ and $f_2(1270)$ are unexpectedly large, or with a model including $f_0(500)$, a doubly charged open-charm tetraquark state $T_{c\bar{s}}^{++}$ and its isospin partner $T_{c\bar{s}}^{0}$. If the former is considered implausible, the $T_{c\bar{s}}$ states are observed with high significance, and the data are consistent with isospin symmetry. When imposing isospin constraints between the two $T_{c\bar{s}}$ states, their mass and width are determined to be $2327\pm13\pm13\,$MeV and $96\pm16\,^{+170}_{-23}\,$MeV, respectively, where the first uncertainty is statistical and the second is systematic. The mass is slightly below the $DK$ threshold, and a spin-parity of $0^+$ is favoured with high significance., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3280/ (LHCb public pages)

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mis-modeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

Federated Learning (FL) offers a promising solution to the privacy concerns associated with centralized Machine Learning (ML) by enabling decentralized, collaborative learning. However, FL is vulnerable to various security threats, including poisoning attacks, where adversarial clients manipulate the training data or model updates to degrade overall model performance. Recognizing this threat, researchers have focused on developing defense mechanisms to counteract poisoning attacks in FL systems. However, existing robust FL methods predominantly focus on computer vision tasks, leaving a gap in addressing the unique challenges of FL with time series data. In this paper, we present FLORAL, a defense mechanism designed to mitigate poisoning attacks in federated learning for time-series tasks, even in scenarios with heterogeneous client data and a large number of adversarial participants. Unlike traditional model-centric defenses, FLORAL leverages logical reasoning to evaluate client trustworthiness by aligning their predictions with global time-series patterns, rather than relying solely on the similarity of client updates. Our approach extracts logical reasoning properties from clients, then hierarchically infers global properties, and uses these to verify client updates. Through formal logic verification, we assess the robustness of each client contribution, identifying deviations indicative of adversarial behavior. Experimental results on two datasets demonstrate the superior performance of our approach compared to existing baseline methods, highlighting its potential to enhance the robustness of FL to time series applications. Notably, FLORAL reduced the prediction error by 93.27% in the best-case scenario compared to the second-best baseline. Our code is available at https://anonymous.4open.science/r/FLORAL-Robust-FTS., Comment: 12 pages, 4 figures, 6 tables

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

The realization of a quantum computer represents a tremendous scientific and technological challenge due to the extreme fragility of quantum information. The physical support of information, namely the quantum bit or qubit, must at the same time be strongly coupled to other qubits by gates to compute information, and well decoupled from its environment to keep its quantum behavior. An interesting physical system for realizing such qubits are magnetic impurities in semiconductors, such as bismuth donors in silicon. Indeed, spins associated to bismuth donors can reach an extremely long coherence time -- of the order of seconds. Yet it is extremely difficult to establish and control efficient gates between these spins. Here we demonstrate a protocol where single bismuth donors can coherently transfer their quantum information to a superconducting flux qubit, which acts as a mediator or quantum bus. This superconducting device allows to connect distant spins on-demand with little impact on their coherent behavior., Comment: 22 pages, 4 figures and 5 extended data figures

Bak, Tang, and Wiesenfeld introduced self-organized criticality with the example of a growing sandpile that reaches then sustains a critical density. They presented the abelian sandpile as a potential model. About a decade later, Dickman, Mu\~noz, Vespignani, and Zapperi claimed that self-organizing sandpile models share their critical densities with parametrized model versions that have conventional phase transitions. Fey, Levine, and Wilson subsequently demonstrated that this fails to occur with the abelian sandpile model. However, the primary subject of Dickman et al.'s work was stochastic sandpile models, and it was widely speculated that their paradigm might still hold in that setting. To this end, we confirm a conjecture of Levine and Silvestri by providing the first rigorous proof that activated random walk in dimension one is driven directly to a critical density corresponding to a parametrized phase transition and then remains there., Comment: 12 pages

We develop a hybrid GNN-CNN architecture for the reconstruction of 3-dimensional continuous cosmological matter fields from discrete point clouds, provided by observed galaxy catalogs. Using the CAMELS hydrodynamical cosmological simulations we demonstrate that the proposed architecture allows for an accurate reconstruction of both the dark matter and electron density given observed galaxies and their features. Our approach includes a learned grid assignment scheme that improves over the traditional cloud-in-cell method. Our method can improve cosmological analyses in situations where non-luminous (and thus unobservable) continuous fields need to be estimated from luminous (observable) discrete point cloud tracers., Comment: 5+5 pages, 6 figures. Contribution to ml4ps workshop at NeurIPS-2024

Recent advances in artificial intelligence (AI) have produced systems capable of increasingly sophisticated performance on cognitive tasks. However, AI systems still struggle in critical ways: unpredictable and novel environments (robustness), lack of transparency in their reasoning (explainability), challenges in communication and commitment (cooperation), and risks due to potential harmful actions (safety). We argue that these shortcomings stem from one overarching failure: AI systems lack wisdom. Drawing from cognitive and social sciences, we define wisdom as the ability to navigate intractable problems - those that are ambiguous, radically uncertain, novel, chaotic, or computationally explosive - through effective task-level and metacognitive strategies. While AI research has focused on task-level strategies, metacognition - the ability to reflect on and regulate one's thought processes - is underdeveloped in AI systems. In humans, metacognitive strategies such as recognizing the limits of one's knowledge, considering diverse perspectives, and adapting to context are essential for wise decision-making. We propose that integrating metacognitive capabilities into AI systems is crucial for enhancing their robustness, explainability, cooperation, and safety. By focusing on developing wise AI, we suggest an alternative to aligning AI with specific human values - a task fraught with conceptual and practical difficulties. Instead, wise AI systems can thoughtfully navigate complex situations, account for diverse human values, and avoid harmful actions. We discuss potential approaches to building wise AI, including benchmarking metacognitive abilities and training AI systems to employ wise reasoning. Prioritizing metacognition in AI research will lead to systems that act not only intelligently but also wisely in complex, real-world situations., Comment: 26 pages, 1 figure, 2 tables

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. High-fidelity modeling of these systems can be achieved with density functional theory molecular dynamics in the two-temperature, adiabatic electron limit. Motivated by this, we construct a statistical mechanics framework for the multi-temperature system that is theoretically consistent with the ab initio calculation. We proceed to derive multi-temperature quantum Ornstein-Zernike equations for the first time. We then construct a two-temperature two-component plasma model using the average atom and compute the radial distribution function, viscosity, ion thermal conductivity, and ion self-diffusion. We verify that we recover the ionic structure and self-diffusion of density functional molecular dynamics simulations., Comment: 12 pages, 7 figures

Myosin motors are fundamental biological actuators, powering diverse mechanical tasks in eukaryotic cells via ATP hydrolysis. Recent work revealed that myosin's velocity-dependent detachment rate can bridge actomyosin dynamics to macroscale Hill muscle predictions. However, the influence of this microscale unbinding, which we characterize by a dimensionless parameter $\alpha$, on macroscale energetic flows-such as power consumption, output and efficiency-remains elusive. Here we develop an analytical model of myosin dynamics that relates unbinding rates $\alpha$ to energetics. Our model agrees with published in-vivo muscle data and, furthermore, uncovers a performance-efficiency tradeoff governed by $\alpha$. To experimentally validate the tradeoff, we build HillBot, a robophysical model of Hill's muscle that mimics nonlinearity. Through HillBot, we decouple $\alpha$'s concurrent effect on performance and efficiency, demonstrating that nonlinearity drives efficiency. We compile 136 published measurements of $\alpha$ in muscle and myoblasts to reveal a distribution centered at $\alpha^* = 3.85 \pm 2.32$. Synthesizing data from our model and HillBot, we quantitatively show that $\alpha^*$ corresponds to a class of generalist actuators that are both relatively powerful and efficient, suggesting that the performance-efficiency tradeoff underpins the prevalence of $\alpha^*$ in nature. We leverage these insights and propose a nonlinear variable-impedance protocol to shift along a performance-efficiency axis in robotic applications., Comment: 23 pages, 6 figures. PDF of supplemental information available in zip download

Proton-neutron pairing and like-nucleon pairing are two different facets of atomic nuclear configurations. While like-nucleon pair condensates manifest their superfluidic nature in semi magic nuclei, it is not absolutely clear if there exists a T=0 proton-neutron pair condensate phase in $N=Z$ nuclei. With an explicit formalism of general pair condensates with good particle numbers, we optimize proton-neutron pair condensates for all $N=Z$ nuclei between $^{16}$O and $^{100}$Sn, given shell model effective interactions. As comparison, we also optimize like-nucleon pair condensates for their semi-magic isotones. Shannon entanglement entropy is a measurement of mixing among pair configurations, and can signal intrinsic phase transition. It turns out the like-nucleon pair condensates for semi-magic nuclei have large entropies signaling an entangled phase, but the proton-neutron pair condensates end up not far from a Hartree-Fock solution, with small entropy. With artificial pairing interaction strengths, we show that the general proton-neutron pair condensate can transit from an entangled T=1 phase to an entangled T=0 phase, i.e. pairing phase transition driven by external parameters. In the T=0 limit, the proton-neutron pair condensate turns out to be a purely P pair condensate with large entanglement entropy, although such cases may occur in cold atom systems, unlikely in atomic nuclei.

The $n=1$ photon ring is an important probe of black hole (BH) properties and will be resolved by the Black Hole Explorer (BHEX) for the first time. However, extraction of black hole parameters from observations of the $n=1$ subring is not trivial. Developing this capability can be achieved by building a sample of $n=1$ subring simulations, as well as by performing feature extraction on this high-volume sample to track changes in the geometry, which presents significant computational challenges. Here, we present a framework for the study of $n=1$ photon ring behavior and BH property measurement from BHEX images. We use KerrBAM to generate a grid of $\gtrsim10^6$ images of $n=1$ photon rings spanning the entire space of Kerr BH spins and inclinations. Intensity profiles are extracted from images using a novel feature extraction method developed specifically for BHEX. This novel method is highly optimized and outperforms existing EHT methods by a factor of ${\sim}3000$. Additionally, we propose a novel, minimal set of geometric measurables for characterizing the behavior of the $n=1$ subring geometry. We apply these measurables to our simulation grid and test spin recovery on simulated images using: (i) gradient boosting, a machine learning algorithm; and (ii) an extension of Deep Horizon, a deep learning framework. We find $\gtrsim90$\% correct recovery of BH properties using the machine/deep learning approaches, and characterize the space of resolution-dependent geometric degeneracies. Finally, we test both approaches on GRMHD simulations of black hole accretion flows, and report accurate recovery of spin at the expected inclination of M87*., Comment: 15 pages, 9 figures, Submitted for publication in ApJ

Salt clouds are predicted to be common on warm exoplanets, but their optical properties are uncertain. The Exoplanet Cloud Ensemble Scattering System (ExCESS), a new apparatus to measure the scattering intensity and degree of linear polarization (DOLP) for an ensemble of particles, is introduced here and used to study the light scattering properties of KCl cloud analogs. ExCESS illuminates particles with a polarized laser beam (532 nm) and uses a photomultiplier tube detector to sweep the plane of illumination. Scattering measurements for KCl particles were collected for three size distributions representative of modeled clouds for the warm exoplanet GJ 1214b. Our measurements show that Lorenz-Mie calculations, commonly used to estimate the light scattering properties of assumedly spherical cloud particles, offer an inaccurate depiction of cubic and cuboid shaped KCl particles. All of our measurements indicate that Lorenz-Mie scattering overestimates the backscattering intensity of our cloud analogs and incorrectly predicts the scattering at mid-phase angles (~90 degrees) and preferential polarization state of KCl scattered light. Our results align with the general scattering properties of non-spherical particles and underscore the importance of further understanding the effects that such particles will have on radiative transfer models of exoplanet atmospheres and reflected light observations of exoplanets by the upcoming Nancy Grace Roman Space Telescope and Habitable Worlds Observatory., Comment: Published in the Planetary Science Journal

Fokker-Planck equations (forward Kolmogorov equations) evolve probability densities in time from an initial condition. For distributions over the real line, these evolution equations can sometimes be transformed into dynamics over the incomplete zeroth and first moments. We call this perspective the Lorenz dynamics of the system after the Lorenz curve description of distributions of wealth. This offers the benefit of presenting the dynamics over a compact domain. The integral transformation is motivated and then stated for a general class of Fokker-Planck equations. Following this, the transformed equation is solved for the heat equation and some variants thereof. Finally, some equations arising from the application of kinetic theory to idealized economic systems are transformed and analyzed in this new light.

This work introduces a novel paradigm for solving optimal control problems for hybrid dynamical systems under uncertainties. Robotic systems having contact with the environment can be modeled as hybrid systems. Controller design for hybrid systems under disturbances is complicated by the discontinuous jump dynamics, mode changes with inconsistent state dimensions, and variations in jumping timing and states caused by noise. We formulate this problem into a stochastic control problem with hybrid transition constraints and propose the Hybrid Path Integral (H-PI) framework to obtain the optimal controller. Despite random mode changes across stochastic path samples, we show that the ratio between hybrid path distributions with varying drift terms remains analogous to the smooth path distributions. We then show that the optimal controller can be obtained by evaluating a path integral with hybrid constraints. Importance sampling for path distributions with hybrid dynamics constraints is introduced to reduce the variance of the path integral evaluation, where we leverage the recently developed Hybrid iterative-Linear-Quadratic-Regulator (H-iLQR) controller to induce a hybrid path distribution proposal with low variance. The proposed method is validated through numerical experiments on various hybrid systems and extensive ablation studies. All the sampling processes are conducted in parallel on a Graphics Processing Unit (GPU)., Comment: 14 pages

We measure the time-integrated CP asymmetry in $D^{0} \rightarrow K^{0}_{S}K^{0}_{S}$ decays reconstructed in $e^{+}e^{-} \rightarrow c\overline{c}$ events collected by the Belle and Belle II experiments. The corresponding data samples have integrated luminosities of 980 fb$^{-1}$ and 428 fb$^{-1}$, respectively. The $D^{0}$ decays are required to originate from the $D^{*+} \rightarrow D^{0}\pi^{+}$ decay, which determines the charm flavor at production time. A control sample of $D^{0} \rightarrow K^{+}K^{-}$ decays is used to correct for production and detection asymmetries. The result, $(-1.4\pm1.3{\rm(stat)}\pm0.1{\rm (syst)})\%$, is consistent with previous determinations and with CP symmetry., Comment: 10 pages, 3 figures. arXiv admin note: text overlap with arXiv:2410.22961

Self-correction is one of the most amazing emerging capabilities of Large Language Models (LLMs), enabling LLMs to self-modify an inappropriate output given a natural language feedback which describes the problems of that output. Moral self-correction is a post-hoc approach correcting unethical generations without requiring a gradient update, making it both computationally lightweight and capable of preserving the language modeling ability. Previous works have shown that LLMs can self-debias, and it has been reported that small models, i.e., those with less than 22B parameters, are not capable of moral self-correction. However, there is no direct proof as to why such smaller models fall short of moral self-correction, though previous research hypothesizes that larger models are skilled in following instructions and understanding abstract social norms. In this paper, we empirically validate this hypothesis in the context of social stereotyping, through meticulous prompting. Our experimental results indicate that (i) surprisingly, 3.8B LLMs with proper safety alignment fine-tuning can achieve very good moral self-correction performance, highlighting the significant effects of safety alignment; and (ii) small LLMs are indeed weaker than larger-scale models in terms of comprehending social norms and self-explanation through CoT, but all scales of LLMs show bad self-correction performance given unethical instructions.

Optical clocks have improved their frequency stability and estimated accuracy by more than two orders of magnitude over the best caesium microwave clocks that realise the SI second. Accordingly, an optical redefinition of the second has been widely discussed, prompting a need for the consistency of optical clocks to be verified worldwide. While satellite frequency links are sufficient to compare microwave clocks, a suitable method for comparing high-performance optical clocks over intercontinental distances is missing. Furthermore, remote comparisons over frequency links face fractional uncertainties of a few $10^{-18}$ due to imprecise knowledge of each clock's relativistic redshift, which stems from uncertainty in the geopotential determined at each distant location. Here, we report a landmark campaign towards the era of optical clocks, where, for the first time, state-of-the-art transportable optical clocks from Japan and Europe are brought together to demonstrate international comparisons that require neither a high-performance frequency link nor information on the geopotential difference between remote sites. Conversely, the reproducibility of the clocks after being transported between countries was sufficient to determine geopotential height offsets at the level of 4 cm. Our campaign paves the way for redefining the SI second and has a significant impact on various applications, including tests of general relativity, geodetic sensing for geosciences, precise navigation, and future timing networks., Comment: 29 pages, 5 figures

We perform a model-independent measurement of the $D^0$-$\overline{D}{}^0$ mixing parameters using samples of $e^+e^-$-collision data collected by the Belle and Belle II experiments that have integrated luminosities of $951\ \text{fb}^{-1}$ and $408\ \text{fb}^{-1}$, respectively. Approximately $2.05\times10^6$ neutral $D$ mesons are reconstructed in the $D^0\rightarrow K^0_{S}\pi^+\pi^-$ channel, with the neutral $D$ flavor tagged by the charge of the pion in the $D^{*+}\rightarrow D^0\pi^+$ decay. Assuming charge-parity symmetry, the mixing parameters are measured to be $ x = (4.0\pm1.7\pm0.4)\times 10^{-3} $ and $ y = (2.9\pm1.4\pm0.3)\times 10^{-3}$, where the first uncertainties are statistical and the second systematic. The results are consistent with previous determinations.

Federated Learning (FL) shows promise in preserving privacy and enabling collaborative learning. However, most current solutions focus on private data collected from a single domain. A significant challenge arises when client data comes from diverse domains (i.e., domain shift), leading to poor performance on unseen domains. Existing Federated Domain Generalization approaches address this problem but assume each client holds data for an entire domain, limiting their practicality in real-world scenarios with domain-based heterogeneity and client sampling. To overcome this, we introduce FISC, a novel FL domain generalization paradigm that handles more complex domain distributions across clients. FISC enables learning across domains by extracting an interpolative style from local styles and employing contrastive learning. This strategy gives clients multi-domain representations and unbiased convergent targets. Empirical results on multiple datasets, including PACS, Office-Home, and IWildCam, show FISC outperforms state-of-the-art (SOTA) methods. Our method achieves accuracy improvements ranging from 3.64% to 57.22% on unseen domains. Our code is available at https://anonymous.4open.science/r/FISC-AAAI-16107.

The single variant spin cycloid and associated antiferromagnetic order in multiferroic BiFeO3 can provide a direct and predictable magnetoelectric coupling to ferroelectric order for deterministic switching, and also a key to fundamental understanding of spin transport and magnon-based applications in the system. (111) oriented BiFeO3 supplies an easy magnetic plane for the spin cycloid, but despite previous efforts, achieving deterministic switching of the single spin cycloid over multiple cycles remains challenging due to the presence of multiple spin cycloid domains in the (111) plane. Here we show that anisotropic in-plane strain engineering can stabilize a single antiferromagnetic domain and provide robust, deterministic switching. We grow BiFeO3 on orthorhombic NdGaO3 (011)o [(111)pc] substrates, breaking the spin cycloid degeneracy and by imposing a uniaxial strain in the (111) plane. This stabilization is confirmed through direct imaging with scanning NV microscopy and non-resonant X-ray diffraction. Remarkably, we achieved deterministic and non-volatile 180{\deg} switching of ferroelectric and associated antiferromagnetic domains over 1,000 cycles, significantly outperforming existing approaches. Our findings underscore that anisotropic strain engineering opens up exciting possibilities for (111)pc monodomain BiFeO3 in potential magnetoelectric and emerging magnonic applications., Comment: 17 pages, 4 figures

The promise of large-scale, high-resolution datasets from Electron Microscopy (EM) and X-ray Microtomography (XRM) lies in their ability to reveal neural structures and synaptic connectivity, which is critical for understanding the brain. Effectively managing these complex and rapidly increasing datasets will enable new scientific insights, facilitate querying, and support secondary use across the neuroscience community. However, without effective neurodata standards that permit use of these data across multiple systems and workflows, these valuable and costly datasets risk being underutilized especially as they surpass petascale levels. These standards will promote data sharing through accessible interfaces, allow researchers to build on each other's work, and guide the development of tools and capabilities that are interoperable. Herein we outline a standards framework for creating and managing annotations originating and derived from high-resolution volumetric imaging and connectomic datasets, focusing on ensuring Findable, Accessible, Interoperable, and Reusable (FAIR) practices. The goal is to enhance collaborative efforts, boost the reliability of findings, and enable comparative analysis across growing datasets of different species and modalities. We have formed a global working group with academic and industry partners in the high-resolution volumetric data generation and analysis community, focused on identifying gaps in current EM and XRM data pipelines, and refining outlines and platforms for standardizing EM and XRM methods. This focus considers existing and past community approaches and includes examining neuronal entities, biological components, and associated metadata, while emphasizing adaptability and fostering collaboration., Comment: 11 pages, 4 figures, 1 table

In this paper, we study the nonlinear wave modulation of arbitrary amplitude periodic traveling wave solutions of the Camassa-Holm (CH) equation. Slow modulations of wave trains is often described through Whitham's theory of modulations, which at leading order models the slow evolution of the fundamental wave characteristics (such as the wave's frequency, mass and momentum) through a disperionless system of quasi-linear partial differential equations. The modulational stability or instability of such a slowly modulated wave is considered to be determined by the hyperbolicity or ellipticity of this Whitham modulation system of equations. In work by Abenda \& Grava, the Whitham modulation system for the CH equation was derived through averaged Lagrangian methods and was further shown to always be hyperbolic (although strict hyperbolicity may fail). In this work, we provide an independent derivation of the Whitham modulation system for the CH equation through nonlinear WKB / multiple scales expansions. We further provide a rigorous connection between the Whitham modulation equations for the CH equation and the spectral stability of the underlying periodic wave train to localized (i.e. integrable on the line) perturbations. In particular, we prove that the strict hyperbolicity of the Whitham system implies spectral stability in a neighborhood of the origin in the spectral plane, i.e. spectral modulational stability. As an illustration of our theory, we examine the Whitham modulation system for wave trains with asymptotically small oscillations about their total mass., Comment: 35 pages, 2 figures

Many nucleosynthetic channels create the elements, but two-parameter models characterized by $\alpha$ and Fe nonetheless predict stellar abundances in the Galactic disk to accuracies of 0.02 to 0.05 dex for most measured elements, near the level of current abundance uncertainties. It is difficult to make individual measurements more precise than this to investigate lower-amplitude nucleosynthetic effects, but population studies of mean abundance patterns can reveal more subtle abundance differences. Here we look at the detailed abundances for 67315 stars from APOGEE DR17, but in the form of abundance residuals away from a best-fit two-parameter, data-driven nucleosynthetic model. We find that these residuals show complex structures with respect to age, guiding radius, and vertical action that are not random and are also not strongly correlated with sources of systematic error such as surface gravity, effective temperature, and radial velocity. The residual patterns, especially in Na, C+N, Ni, Mn, and Ce, trace kinematic structures in the Milky Way, such as the inner disk, thick disk, and flared outer disk. A principal component analysis suggests that most of the observed structure is low-dimensional and can be explained by a few eigenvectors. We find that some, but not all, of the effects in the low-$\alpha$ disk can be explained by dilution with fresh gas, so that abundance ratios resemble those of stars with higher metallicity. The patterns and maps we provide could be combined with accurate forward models of nucleosynthesis, star formation, and gas infall to provide a more detailed picture of star and element formation in different Milky Way components.

The Milky Way hosts at least two modes in its present day distribution of Fe and alpha-elements. The exact cause of this bimodality is disputed, but one class of explanations involves the merger between the Milky Way and a relatively massive satellite (Gaia-Sausage-Enceladus) at z~2. However, reproducing this bimodality in simulations is not straightforward, with conflicting results on the prevalance, morphology, and mechanism behind multimodality. We present a case study of a galaxy in the Illustris TNG50 simulation which undergoes sequential phases of starburst, brief quiescence, and then rejuvenation. This scenario results in a pronounced abundance bimodality after a post-processing adjustment of the [alpha/Fe] of old stars designed to mimic a higher star formation efficiency in dense gas. The high- and low-alpha sequences are separated in time by the brief quiescent period, which is not associated with a merger but by the formation of a bar followed by AGN activity. This galaxy indicates a novel scenario in which the alpha-bimodality in the Milky Way is caused by the formation of the bar via AGN-induced quenching. In addition to a stellar age gap in the Milky Way, we predict that abundance bimodalities should be more common in barred as opposed to unbarred galaxies., Comment: 13+10 pages, 5+18 figures, to be submitted to ApJ; comments welcome

Technological trends show that Radio Frequency Reinforcement Learning (RFRL) will play a prominent role in the wireless communication systems of the future. Applications of RFRL range from military communications jamming to enhancing WiFi networks. Before deploying algorithms for these purposes, they must be trained in a simulation environment to ensure adequate performance. For this reason, we previously created the RFRL Gym: a standardized, accessible tool for the development and testing of reinforcement learning (RL) algorithms in the wireless communications space. This environment leveraged the OpenAI Gym framework and featured customizable simulation scenarios within the RF spectrum. However, the RFRL Gym was limited to training a single RL agent per simulation; this is not ideal, as most real-world RF scenarios will contain multiple intelligent agents in cooperative, competitive, or mixed settings, which is a natural consequence of spectrum congestion. Therefore, through integration with Ray RLlib, multi-agent reinforcement learning (MARL) functionality for training and assessment has been added to the RFRL Gym, making it even more of a robust tool for RF spectrum simulation. This paper provides an overview of the updated RFRL Gym environment. In this work, the general framework of the tool is described relative to comparable existing resources, highlighting the significant additions and refactoring we have applied to the Gym. Afterward, results from testing various RF scenarios in the MARL environment and future additions are discussed., Comment: Accepted to IEEE CCNC 2025

WASP-12 b is an ultra-hot Jupiter (UHJ) of special interest for atmospheric studies since it is on an inspiraling orbit in an extreme environment of intense radiation and circumstellar gas. Previously claimed detections of active mass loss from this planet are controversial across the literature. To address this controversy, we obtain two new transit observations of WASP-12 b with the optical high-resolution PEPSI spectrograph on the Large Binocular Telescope. Contrary to previous work, we do not observe planetary H$\alpha$ absorption and rule out the amplitude of previously reported detections. Our non-detection may be limited by the sensitivity of our data or could indicate weaker mass loss than suggested by previous studies. We conduct injection-recovery experiments to place constraints on the radial extent of WASP-12 b's escaping atmosphere as probed by Balmer lines, but find that our data do not have the sensitivity to probe down to the planet's Roche Lobe. Using physically motivated models of atmospheric escape, we explore upper limit constraints on the planet's mass-loss rate and deem the data quality in the wavelength regime of Balmer lines insufficient to determine a physically meaningful constraint. We also conduct a spectral survey of other optical absorbers to trace atmospheric circulation but detect no additional absorption. We conclude that previous claims of H$\alpha$ absorption from the atmosphere of WASP-12 b should be reevaluated. Given the anticipated line strength of Balmer/optical features, observing the atmosphere of this faint target will require stacking more observations even with the largest telescope facilities available., Comment: 15 pages, 8 figures, accepted for publication to MNRAS

We present new stellar population models, $\alpha$-MC, self-consistently taking into account non-solar $\rm [\alpha/Fe]$ abundances for both isochrones and stellar spectra. The $\alpha$-MC models are based on $\alpha$-enhanced MIST isochrones and C3K spectral libraries, which are publicly available in FSPS. Our new models cover a wide range of ages ($\rm \log (age/yr) = 5.0 - 10.3$), metallicities ($\rm [Fe/H]=[-2.5,+0.5]$ in steps of 0.25, $\rm [\alpha/Fe]=-0.2,+0.0,+0.2,+0.4,+0.6$), and wavelengths ($0.1-2.5\,\rm \mu m$). We investigate the separate and combined effects of $\alpha$-enhanced isochrones and stellar spectral libraries on simple stellar populations (SSPs), including their broadband colors, spectral indices, and full spectra. We find that the primary effect of $\alpha$-enhancement in isochrones is to lower the overall continuum levels and redden the continuum shapes, while $\alpha$-enhancement in stellar spectra mainly affects individual spectral lines. At constant $\rm [Fe/H]$, $\alpha$-enhancement has significant impacts on the broadband colors by $\rm \sim 0.1-0.4\,mag$ across all ages ($\rm 0.01 - 10\,Gyr$). The effects of $\alpha$-enhancement on colors at fixed $\rm [Z/H]$ are smaller, by $\rm \sim 0.1-0.2\,mag$. The spectral indices involving $\alpha$-elements, Ca4227 and Mg b, increase with $\rm [\alpha/Fe]$ (both at fixed $\rm [Fe/H]$ and fixed $\rm [Z/H]$) due to enhanced $\alpha$-abundances. At constant $\rm [Fe/H]$, $\alpha$-enhancement weakens most Fe-sensitive and Hydrogen Balmer lines. Our new self-consistent $\alpha$-enhanced models will be essential in deriving accurate physical properties of high-redshift galaxies, where $\alpha$-enhancement is expected to be common., Comment: Submitted to ApJ. Comments welcome

We present the Variable Star PhasE Curve (VSPEC) Collection, a set of Python packages for simulating combined-light spectroscopic observations of 3-dimensional exoplanet atmospheres in the presence of stellar variability and inhomogeneity. VSPEC uses the Planetary Spectrum Generator's Global Emission Spectra (PSG/GlobES) application along with a custom-built multi-component time-variable stellar model based on a user-defined grid of stellar photosphere models to produce spectroscopic light curves of the planet-host system. VSPEC can be a useful tool for modeling observations of exoplanets in transiting geometries (primary transit, secondary eclipse) as well as orbital phase curve measurements, and is built in a modular and flexible configuration for easy adaptability to new stellar and planetary model inputs. We additionally present a set of codes developed alongside the core VSPEC modules, including the stellar surface model generator vspec-vsm, the stellar spectral grid interpolation code GridPolator, and a Python interface for PSG, libpypsg., Comment: 18 pages, 11 Figures. To be published in Astronomy & Computing