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A wealth of literature shows positive outcomes and experiences from arts learning, yet youth access to arts education has become significantly more inequitable over the past 30 years. Alongside the growing discourse around arts learning and equity issues, there is a recognized and persistent need for more research. We conducted a critical, qualitative study of out-of-school time (OST) arts organizations across the United States. Our primary research questions were: (1) How do community youth arts organizational leaders, teaching artists, and participants describe the leading ideas and practices in OST youth arts programming? (2) How can OST youth arts work center the cultural, historical, and geographic resources that artists and arts organizations bring to arts programming? We first developed a theoretical framework for understanding arts practices in education and summarize key learning outcomes associated with youth participation in the arts. We then talked with OST arts education experts across the United States to understand how their programs support and center youth in arts learning, particularly Black youth, Indigenous youth, and youth of color (BIPOC youth), youth from low-income backgrounds, and LGBTQIA+ youth. This report offers the concept of "cultural-regional scenes" to describe the critical, qualitative case studies we developed of OST youth arts practice. We describe four unique cultural-regional scenes--the Urban Midwest, the Bay Area, Texas-Mexico Border Towns, and the Indigenous Southwest--and provide examples of youth arts practice in each scene. We conclude with ideas that stretch across scenes and suggest that researchers and practitioners can take up this approach in the study of OST youth arts programs. [Written in collaboration with community artists and artist-leaders across the United States and Indigenous Nations.]

Washington has made some strides in recent years toward increasing awareness and state support of students' basic needs but has lacked state and regional information to drive larger-scale policies, programs, and investments to address the attainment barriers associated with basic needs insecurity. State and regional data on unmet basic needs can help Washington more effectively tackle basic needs barriers to postsecondary attainment by: (1) increasing awareness of the true scale of basic needs insecurity, particularly in communities and education sectors where it may be "invisible" or counter to popular perception; (2) pointing to disparate impacts in particular student populations through the lenses of student status, race/ethnicity, veteran, or employment status, etc.; and (3) serving as an advocacy tool for data-driven solutions on campus, regional, and state levels. To address this information gap, in 2021 a statewide Basic Needs Data Work Group proposed a coordinated basic needs survey across Washington higher education institutions. The Washington Student Experience survey reported on here identified considerable levels of basic needs insecurity among college students across the state. In addition, the survey highlighted significant disparities for certain student groups, especially American Indian/Alaska Native students, Black/African-American students, low-income students, students with disability, students with dependents, and former foster youth. [The administration of the Washington Student Experience Survey and the development of this report were completed by staff at Western Washington University.]

The life cycle of most marine invertebrates includes a planktonic larval stage before metamorphosis to bottom-dwelling adulthood. During larval stage, ciliary-mediated activity enables feeding (capture unicellular algae) and transport of materials (oxygen) required for the larva's growth, development, and successful metamorphosis. Investigating the underlying hydrodynamics of these behaviors is valuable for addressing fundamental biological questions (e.g., phenotypic plasticity) and advancing engineering applications. In this work, we combined microfluidics and fluorescence microscopy as a miniaturized PIV (mPIV) to study ciliary-medicated hydrodynamics during suspension feeding in sand dollar larvae (Dendraster excentricus). First, we confirmed the approach's feasibility by examining the underlying hydrodynamics (vortex patterns) for low- and high-fed larvae. Next, ciliary hydrodynamics were tracked from 11 days post-fertilization (DPF) to 20 DPF for 21 low-fed larvae. Microfluidics enabled the examination of baseline activities (without external flow) and behaviors in the presence of environmental cues (external flow). A library of qualitative vortex patterns and quantitative hydrodynamics was generated and shared as a stand alone repository. Results from mPIV (velocities) were used to examine the role of ciliary activity in transporting materials (oxygen). Given the laminar flow and the viscosity-dominated environments surrounding the larvae, overcoming the diffusive boundary layer is critical for the organism's survival. Peclet number analysis for oxygen transport suggested that ciliary velocities help overcome the diffusion dominated transport (max Pe numbers between 30-60). Microfluidics serving as mPIV provided a scalable and accessible approach for investigating the ciliary hydrodynamics of marine organisms., Comment: 21 pages and 11 figures (videos not included)

Gate-defined quantum dots are a promising candidate system for realizing scalable, coupled qubit systems and serving as a fundamental building block for quantum computers. However, present-day quantum dot devices suffer from imperfections that must be accounted for, which hinders the characterization, tuning, and operation process. Moreover, with an increasing number of quantum dot qubits, the relevant parameter space grows sufficiently to make heuristic control infeasible. Thus, it is imperative that reliable and scalable autonomous tuning approaches are developed. This meeting report outlines current challenges in automating quantum dot device tuning and operation with a particular focus on datasets, benchmarking, and standardization. We also present insights and ideas put forward by the quantum dot community on how to overcome them. We aim to provide guidance and inspiration to researchers invested in automation efforts., Comment: A meeting report from a workshop held at the National Institute of Standards and Technology, Gaithersburg, MD

Embedding rare-earth pnictide (RE-V) nanoparticles into III-V semiconductors enables unique optical, electrical, and thermal properties, with applications in THz photoconductive switches, tunnel junctions, and thermoelectric devices. Despite the high structural quality and control over growth, particle size, and density, the underlying electronic structure of these nanocomposite materials has only been hypothesized. Basic questions about the metallic or semiconducting nature of the nanoparticles (that are typically < 3 nm in diameter) have remained unanswered. Using first-principles calculations, we investigated the structural and electronic properties of ErAs nanoparticles in AlAs, GaAs, InAs, and their alloys. Formation energies of the ErAs nanoparticles with different shapes and sizes (i.e., from cubic to spherical, with 1.14 nm, 1.71 nm, and 2.28 nm diameters) show that spherical nanoparticles are the most energetically favorable. As the diameter increases, the Fermi level is lowered from near the conduction band to the middle of the gap. For the lowest energy nanoparticles, the Fermi level is pinned near the mid-gap, at about 0.8 eV above the valence band in GaAs and about 1.2 eV in AlAs, and it is resonant in the conduction band in InAs. Our results show that the Fermi level is pinned on an absolute energy scale once the band alignment at AlAs/GaAs/InAs interfaces is considered, offering insights into the rational design of these nanocomposite materials.

Galactic fountains driven by star formation result in a variety of kinematic structures such as ionised winds and thick gas disks, both of which manifest as complex emission line profiles that can be parametrised by multiple Gaussian components. We use integral field spectroscopy (IFS) from the SAMI Galaxy Survey to spectrally resolve these features, traced by broad H$\alpha$ components, and distinguish them from the star-forming thin disk, traced by narrow components, in 3068 galaxies in the local Universe. Using a matched sample analysis technique, we demonstrate that the presence of complex emission line profiles in star-forming galaxies is most strongly correlated with the global star formation rate (SFR) surface density of the host galaxy measured within $1R_{\rm e}$ ($\Sigma_{{\rm SFR},R_{\rm e}}$), even when controlling for both observational biases, including inclination, amplitude-to-noise and angular scale, and sample biases in parameters such as stellar mass and SFR. Leveraging the spatially resolved nature of the dataset, we determine that the presence of complex emission line profiles within individual spaxels is driven not only by the local $\Sigma_{\rm SFR}$, but by the $\Sigma_{{\rm SFR},R_{\rm e}}$ of the host galaxy. We also parametrise the clumpiness of the SFR within individual galaxies, and find that $\Sigma_{{\rm SFR},R_{\rm e}}$ is a stronger predictor of the presence of complex emission line profiles than clumpiness. We conclude that, with a careful treatment of observational effects, it is possible to identify structures traced by complex emission line profiles, including winds and thick ionised gas disks, at the spatial and spectral resolution of SAMI using the Gaussian decomposition technique., Comment: 21 pages, 17 figures, accepted for publication in MNRAS

Nanostructures represent a frontier where meticulous attention to the control and assessment of structural dimensions becomes a linchpin for their seamless integration into diverse technological applications. By using integrative and comprehensive methodical series of studies, we investigate the evolution of the depolarization factors in the anisotropic Bruggeman effective medium approximation, that are extremely sensitive to the changes in critical dimensions of the nanostructure platforms. To this end, we fabricate spatially coherent highly-ordered slanted nanocolumns from zirconia, silicon, titanium, and permalloy on silicon substrates with varying column lengths using glancing angle deposition. In tandem, broad-spectral range Mueller matrix spectroscopic ellipsometry data, spanning from the near-infrared to the vacuum ultraviolet (0.72 eV to 6.5 eV), is analyzed with a best-match model approach based on the anisotropic Bruggeman effective medium theory. We thereby extracted the anisotropic optical properties including complex dielectric function, birefringence, and dichroism. Most notably, our research unveils a universal, material-independent inverse relationship between depolarization factors and column length. We envision that the presented universal relationship will permit accurate prediction of optical properties of nanocolumnar thin films improving their integration and optimization for optoelectronic and photonic device applications., Comment: 20 pages, 10 figures

Given the increasing prevalence of wildland fires in the Western US, there is a critical need to develop tools to understand and accurately predict burn severity. We develop a machine learning model to predict post-fire burn severity using pre-fire remotely sensed data. Hydrological, ecological, and topographical variables collected from four regions of California - the sites of the Kincade fire (2019), the CZU Lightning Complex fire (2020), the Windy fire (2021), and the KNP Fire (2021) - are used as predictors of the difference normalized burn ratio. We hypothesize that a Super Learner (SL) algorithm that accounts for spatial autocorrelation using Vecchia's Gaussian approximation will accurately model burn severity. In all combinations of test and training sets explored, the results of our model showed the SL algorithm outperformed standard Linear Regression methods. After fitting and verifying the performance of the SL model, we use interpretable machine learning tools to determine the main drivers of severe burn damage, including greenness, elevation and fire weather variables. These findings provide actionable insights that enable communities to strategize interventions, such as early fire detection systems, pre-fire season vegetation clearing activities, and resource allocation during emergency responses. When implemented, this model has the potential to minimize the loss of human life, property, resources, and ecosystems in California., Comment: 18 pages, 3 figures

This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw), held in July 2023. A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal, and policy challenges presented by law for Generative AI, and by Generative AI for law, with an emphasis on U.S. law in particular. We begin the report with a high-level statement about why Generative AI is both immensely significant and immensely challenging for law. To meet these challenges, we conclude that there is an essential need for 1) a shared knowledge base that provides a common conceptual language for experts across disciplines; 2) clarification of the distinctive technical capabilities of generative-AI systems, as compared and contrasted to other computer and AI systems; 3) a logical taxonomy of the legal issues these systems raise; and, 4) a concrete research agenda to promote collaboration and knowledge-sharing on emerging issues at the intersection of Generative AI and law. In this report, we synthesize the key takeaways from the GenLaw workshop that begin to address these needs. All of the listed authors contributed to the workshop upon which this report is based, but they and their organizations do not necessarily endorse all of the specific claims in this report.

In today's rapidly evolving technological landscape and advanced software development, the rise in cyber security attacks has become a pressing concern. The integration of robust cyber security defenses has become essential across all phases of software development. It holds particular significance in identifying critical cyber security vulnerabilities at the initial stages of the software development life cycle, notably during the requirement phase. Through the utilization of cyber security repositories like The Common Attack Pattern Enumeration and Classification (CAPEC) from MITRE and the Common Vulnerabilities and Exposures (CVE) databases, attempts have been made to leverage topic modeling and machine learning for the detection of these early-stage vulnerabilities in the software requirements process. Past research themes have returned successful outcomes in attempting to automate vulnerability identification for software developers, employing a mixture of unsupervised machine learning methodologies such as LDA and topic modeling. Looking ahead, in our pursuit to improve automation and establish connections between software requirements and vulnerabilities, our strategy entails adopting a variety of supervised machine learning techniques. This array encompasses Support Vector Machines (SVM), Na\"ive Bayes, random forest, neural networking and eventually transitioning into deep learning for our investigation. In the face of the escalating complexity of cyber security, the question of whether machine learning can enhance the identification of vulnerabilities in diverse software development scenarios is a paramount consideration, offering crucial assistance to software developers in developing secure software.

Photonics offer numerous functionalities that can be used to realize astrophotonic instruments. The most spectacular example to date is the ESO Gravity instrument at the Very Large Telescope in Chile. Integrated astrophotonic devices stand to offer critical advantages for instrument development, including extreme miniaturization, as well as integration, superior thermal and mechanical stabilization owing to the small footprint, and high replicability offering cost savings. Numerous astrophotonic technologies have been developed to address shortcomings of conventional instruments to date, including for example the development of photonic lanterns, complex aperiodic fiber Bragg gratings, complex beam combiners to enable long baseline interferometry, and laser frequency combs for high precision spectral calibration of spectrometers. Despite these successes, the facility implementation of photonic solutions in astronomical instrumentation is currently limited because of (1) low throughputs from coupling to fibers, coupling fibers to chips, propagation and bend losses, device losses, etc, (2) difficulties with scaling to large channel count devices needed for large bandwidths and high resolutions, and (3) efficient integration of photonics with detectors, to name a few. In this roadmap, we identify 24 areas that need further development. We outline the challenges and advances needed across those areas covering design tools, simulation capabilities, fabrication processes, the need for entirely new components, integration and hybridization and the characterization of devices. To realize these advances the astrophotonics community will have to work cooperatively with industrial partners who have more advanced manufacturing capabilities. With the advances described herein, multi-functional instruments will be realized leading to novel observing capabilities for both ground and space platforms., Comment: 191 pages, 47 figures. This is the version of the article before peer review or editing, as submitted by an author to J. Phys. Photonics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://iopscience.iop.org/article/10.1088/2515-7647/ace869/meta

The final sizes, composition, and angular momenta of solid planetary bodies depend on the outcomes of collisions between planetary embryos. The most common numerical method for simulating embryo collisions is to combine a gravity solver with a hydrodynamic solver, allowing pressure gradients, shock waves, and gravitational torques to loft material into orbit. Here, we perform the first direct comparison between hydrodynamic methods and a simplified method employing only gravity and a quadratic repulsive force. The formation of Earth's Moon, perhaps the most heavily simulated planetary collision, is used as a test case. Many of the main features of a collision between two planetary embryos, including collisions in which an orbiting disc of material and/or intact moons are formed, are controlled solely by gravitational forces. Comparison of the methods shows that the mass and orbit of the satellite, as well as the extent of physical mixing between the protoearth and impactor, are similar regardless of the inclusion of the inclusion of hydrodynamic effects or the equation of state employed. The study of thermal and chemical effects of the impact, and determining the time scale for lunar accretion, still require a full hydrodynamic calculation. The simplified gravity plus quadratic repulsive force approach allows rapid testing of various initial conditions to identify cases for further detailed study., Comment: 10 pages, 4 figures, submitted to MNRAS

The existence of a plateau in the short-duration tail of the observed distribution of cosmological Long-soft Gamma Ray Bursts (LGRBs) has been argued as the first direct evidence of Collapsars. A similar plateau in the short-duration tail of the observed duration distribution of Short-hard Gamma Ray Bursts (SGRBs) has been suggested as evidence of compact binary mergers. We present an equally plausible alternative interpretation for this evidence, which is purely statistical. Specifically, we show that the observed plateau in the short-duration tail of the duration distribution of LGRBs can naturally occur in the statistical distributions of strictly positive physical quantities, exacerbated by the effects of mixing with the duration distribution of SGRBs, observational selection effects, and data aggregation (e.g., binning) methodologies. The observed plateau in the short-duration tail of the observed distributions of SGRBs can similarly result from a combination of sample incompleteness and inhomogeneous binning of data. The observed plateau in the short-duration tail of the observed distributions of SGRBs can similarly result from a combination of sample incompleteness and inhomogeneous binning of data. We further confirm the impact of these factors on the observation of a plateau in the duration distributions of Gamma-Ray Bursts (GRBs) through extensive numerical Monte Carlo simulations. Our presented analysis corroborates and strengthens a purely statistical and sample-incompleteness interpretation of the observed plateau in the duration distribution of LGRBs and SGRBs without invoking the physics of Collapsars and jet-propagation through the stellar envelope., Comment: Accepted by A&A

The inner hundred parsecs of the Milky Way hosts the nearest supermassive black hole, largest reservoir of dense gas, greatest stellar density, hundreds of massive main and post main sequence stars, and the highest volume density of supernovae in the Galaxy. As the nearest environment in which it is possible to simultaneously observe many of the extreme processes shaping the Universe, it is one of the most well-studied regions in astrophysics. Due to its proximity, we can study the center of our Galaxy on scales down to a few hundred AU, a hundred times better than in similar Local Group galaxies and thousands of times better than in the nearest active galaxies. The Galactic Center (GC) is therefore of outstanding astrophysical interest. However, in spite of intense observational work over the past decades, there are still fundamental things unknown about the GC. JWST has the unique capability to provide us with the necessary, game-changing data. In this White Paper, we advocate for a JWST NIRCam survey that aims at solving central questions, that we have identified as a community: i) the 3D structure and kinematics of gas and stars; ii) ancient star formation and its relation with the overall history of the Milky Way, as well as recent star formation and its implications for the overall energetics of our galaxy's nucleus; and iii) the (non-)universality of star formation and the stellar initial mass function. We advocate for a large-area, multi-epoch, multi-wavelength NIRCam survey of the inner 100\,pc of the Galaxy in the form of a Treasury GO JWST Large Program that is open to the community. We describe how this survey will derive the physical and kinematic properties of ~10,000,000 stars, how this will solve the key unknowns and provide a valuable resource for the community with long-lasting legacy value., Comment: This White Paper will be updated when required (e.g. new authors joining, editing of content). Most recent update: 24 Oct 2023

Context. Multi-wavelength studies of galaxies and galactic nuclei allow us to build a relatively more complete picture of the interstellar medium (ISM), especially in the dusty regions of starburst galaxies. An understanding of the physical processes in nearby galaxies can assist in the study of more distant sources at higher redshifts, which cannot be resolved. Aims. We aimed to use observations presented in the first part of this series of papers to model the physical conditions of the ISM in the nuclear region of NGC 253, in order to obtain primary parameters such as gas densities and metallicities. From the created model we further calculated secondary parameters such as gas masses of the different phases, and estimated the fraction of [C II] 158 um from the different phases, which allowed us to probe the nuclear star-formation rate. Methods. To compare theory with our observations we used MULTIGRIS, a probabilistic tool that determines probabilities for certain ISM parameters from a grid of Cloudy models together with a set of spectroscopic lines. Results. We find that the hypothetical active galactic nucleus within NGC 253 has only a minor impact compared to the starburst on the heating of the ISM as probed by the observed lines. We characterise the ISM and obtain parameters such as a solar metallicity, a mean density of ~230cm-3 , an ionisation parameter of log U = -3, and an age of the nuclear cluster of ~2 Myr. Furthermore, we estimate the masses of the ionised (3.8 x 10^6 M_sol ), neutral atomic (9.1 x 10^6 M_sol ), and molecular (2.0 x 10^8 M_sol ) gas phases as well as the dust mass (1.8 x 10^6 M_sol ) in the nucleus of NGC 253., Comment: Accepted for publication in A&A; 15 pages, 10 Figures, 6 Tables