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Boosting literacy among school-age children remains a national priority. Nearly one third of students in the United States have not developed the foundational reading skills needed to succeed academically, with students living in poverty, students with disabilities, and English learners especially at risk. Starting in 2010, Congress invested more than $1 billion for state literacy improvement efforts through the Striving Readers Comprehensive Literacy (SRCL) program. SRCL was intended to focus funding on disadvantaged schools, encourage schools to use evidence-based practices, and support schools and teachers in providing comprehensive literacy instruction. These efforts were expected to lead to improved literacy outcomes for students. This study assesses how well SRCL implementation was aligned with these goals, using information collected from states, districts, and schools in all 11 states awarded grants in 2017.

This paper introduces VIVRA (Voice Interactive Virtual Reality Annotation), a VR application combining multimodal interaction with large language models (LLMs) to transform users' ideas into interactive 3D visualizations. VIVRA converts verbalized thoughts into "idea balloons" that summarize and expand on detected topics by an LLM. VIVRA allows users to verbalize their thoughts in real time or record their ideas to display the topics later. We evaluated the effectiveness of VIVRA in an exploratory study with 29 participants and a user study with 10 participants. Our results show that VIVRA enhanced users' ability to reflect on and develop ideas, achieving high levels of satisfaction, usability, and engagement. Participants valued VIVRA as a reflective tool for exploring personal thoughts and ideas. We discuss the potential advantages and uses of this application, highlighting the potential of combining immersive technologies with LLMs to create powerful ideation and reflection tools., Comment: 24 pages, 6 figures

In environmental epidemiology, identifying subpopulations vulnerable to chemical exposures and those who may benefit differently from exposure-reducing policies is essential. For instance, sex-specific vulnerabilities, age, and pregnancy are critical factors for policymakers when setting regulatory guidelines. However, current semi-parametric methods for heterogeneous treatment effects are often limited to binary exposures and function as black boxes, lacking clear, interpretable rules for subpopulation-specific policy interventions. This study introduces a novel method using cross-validated targeted minimum loss-based estimation (TMLE) paired with a data-adaptive target parameter strategy to identify subpopulations with the most significant differential impact from simulated policy interventions that reduce exposure. Our approach is assumption-lean, allowing for the integration of machine learning while still yielding valid confidence intervals. We demonstrate the robustness of our methodology through simulations and application to NHANES data. Our analysis of NHANES data for persistent organic pollutants on leukocyte telomere length (LTL) identified age as the maximum effect modifier. Specifically, we found that exposure to 3,3',4,4',5-pentachlorobiphenyl (pcnb) consistently had a differential impact on LTL, with a one standard deviation reduction in exposure leading to a more pronounced increase in LTL among younger populations compared to older ones. We offer our method as an open-source software package, \texttt{EffectXshift}, enabling researchers to investigate the effect modification of continuous exposures. The \texttt{EffectXshift} package provides clear and interpretable results, informing targeted public health interventions and policy decisions.

Estimating the marginally adjusted dose-response curve for continuous treatments is a longstanding statistical challenge critical across multiple fields. In the context of parametric models, mis-specification may result in substantial bias, hindering the accurate discernment of the true data generating distribution and the associated dose-response curve. In contrast, non-parametric models face difficulties as the dose-response curve isn't pathwise differentiable, and then there is no $\sqrt{n}$-consistent estimator. The emergence of the Highly Adaptive Lasso (HAL) MLE by van der Laan [2015] and van der Laan [2017] and the subsequent theoretical evidence by van der Laan [2023] regarding its pointwise asymptotic normality and uniform convergence rates, have highlighted the asymptotic efficacy of the HAL-based plug-in estimator for this intricate problem. This paper delves into the HAL-based plug-in estimators, including those with cross-validation and undersmoothing selectors, and introduces the undersmoothed smoothness-adaptive HAL-based plug-in estimator. We assess these estimators through extensive simulations, employing detailed evaluation metrics. Building upon the theoretical proofs in van der Laan [2023], our empirical findings underscore the asymptotic effectiveness of the undersmoothed smoothness-adaptive HAL-based plug-in estimator in estimating the marginally adjusted dose-response curve.

We construct and enumerate all crepant resolutions of hyperpolygon spaces, a family of conical symplectic singularities arising as Nakajima quiver varieties associated to a star-shaped quiver. We provide an explicit presentation of the Cox ring of any such crepant resolution. Using techniques developed by Arzhantsev-Derenthal-Hausen-Laface we construct all crepant resolutions of the hyperpolygon spaces, including those which are not projective over the singularity. We find that the number of crepant resolutions equals the Ho\c{s}ten-Morris numbers. In proving these results, we obtain a description of all complete geometric quotients associated to the classical GIT problem constructing moduli spaces of ordered points on the projective line. These moduli spaces appear as the Lagrangian subvarieties of crepant resolutions of hyperpolygon spaces fixed under the conical action., Comment: Corrected statements of Lemma 2.28 and Corollary 4.11 and completed arguments in step 6 of the proof of Theorem 5.8

The average treatment effect (ATE) is a common parameter estimated in causal inference literature, but it is only defined for binary treatments. Thus, despite concerns raised by some researchers, many studies seeking to estimate the causal effect of a continuous treatment create a new binary treatment variable by dichotomizing the continuous values into two categories. In this paper, we affirm binarization as a statistically valid method for answering causal questions about continuous treatments by showing the equivalence between the binarized ATE and the difference in the average outcomes of two specific modified treatment policies. These policies impose cut-offs corresponding to the binarized treatment variable and assume preservation of relative self-selection. Relative self-selection is the ratio of the probability density of an individual having an exposure equal to one value of the continuous treatment variable versus another. The policies assume that, for any two values of the treatment variable with non-zero probability density after the cut-off, this ratio will remain unchanged. Through this equivalence, we clarify the assumptions underlying binarization and discuss how to properly interpret the resulting estimator. Additionally, we introduce a new target parameter that can be computed after binarization that considers the status-quo world. We argue that this parameter addresses more relevant causal questions than the traditional binarized ATE parameter. Finally, we present a simulation study to illustrate the implications of these assumptions when analyzing data and to demonstrate how to correctly implement estimators of the parameters discussed.

We present two approaches to constructing isoparametric Virtual Element Methods of arbitrary order for linear elliptic partial differential equations on general two-dimensional domains. The first method approximates the variational problem transformed onto a computational reference domain. The second method computes a virtual domain and uses bespoke polynomial approximation operators to construct a computable method. Both methods are shown to converge optimally, a behaviour confirmed in practice for the solution of problems posed on curved domains.

Learning companion robots for young children are increasingly adopted in informal learning environments. Although parents play a pivotal role in their children's learning, very little is known about how parents prefer to incorporate robots into their children's learning activities. We developed prototype capabilities for a learning companion robot to deliver educational prompts and responses to parent-child pairs during reading sessions and conducted in-home user studies involving 10 families with children aged 3-5. Our data indicates that parents want to work with robots as collaborators to augment parental activities to foster children's learning, introducing the notion of parent-robot collaboration. Our findings offer an empirical understanding of the needs and challenges of parent-child interaction in informal learning scenarios and design opportunities for integrating a companion robot into these interactions. We offer insights into how robots might be designed to facilitate parent-robot collaboration, including parenting policies, collaboration patterns, and interaction paradigms.

Scoliosis, a prevalent condition characterized by abnormal spinal curvature leading to deformity, requires precise assessment methods for effective diagnosis and management. The Cobb angle is a widely used scoliosis quantification method that measures the degree of curvature between the tilted vertebrae. Yet, manual measuring of Cobb angles is time-consuming and labor-intensive, fraught with significant interobserver and intraobserver variability. To address these challenges and the lack of interpretability found in certain existing automated methods, we have created fully automated software that not only precisely measures the Cobb angle but also provides clear visualizations of these measurements. This software integrates deep neural network-based spine region detection and segmentation, spine centerline identification, pinpointing the most significantly tilted vertebrae, and direct visualization of Cobb angles on the original images. Upon comparison with the assessments of 7 expert readers, our algorithm exhibited a mean deviation in Cobb angle measurements of 4.17 degrees, notably surpassing the manual approach's average intra-reader discrepancy of 5.16 degrees. The algorithm also achieved intra-class correlation coefficients (ICC) exceeding 0.96 and Pearson correlation coefficients above 0.944, reflecting robust agreement with expert assessments and superior measurement reliability. Through the comprehensive reader study and statistical analysis, we believe this algorithm not only ensures a higher consensus with expert readers but also enhances interpretability and reproducibility during assessments. It holds significant promise for clinical application, potentially aiding physicians in more accurate scoliosis assessment and diagnosis, thereby improving patient care., Comment: 17 pages, 5 figures

Generative artificial intelligence (AI) and large language models (LLMs) have gained rapid popularity through publicly available tools such as ChatGPT. The adoption of LLMs for personal and professional use is fueled by the natural interactions between human users and computer applications such as ChatGPT, along with powerful summarization and text generation capabilities. Given the widespread use of such generative AI tools, in this work we investigate how these tools can be deployed in a non-safety critical, strategic traffic flow management setting. Specifically, we train an LLM, CHATATC, based on a large historical data set of Ground Delay Program (GDP) issuances, spanning 2000-2023 and consisting of over 80,000 GDP implementations, revisions, and cancellations. We test the query and response capabilities of CHATATC, documenting successes (e.g., providing correct GDP rates, durations, and reason) and shortcomings (e.g,. superlative questions). We also detail the design of a graphical user interface for future users to interact and collaborate with the CHATATC conversational agent., Comment: 8 pages, 5 figures; minor revisions to address reviewer feedback for final submission to the 11th International Conference on Research in Air Transportation (ICRAT)

With the goal of matching spacecraft measurements from Juno and Galileo missions, we construct ensembles of 2, 3, 4, 5, and 6 layer models for Jupiter's interior. All except our two layer models can match the planet's gravity field as measured by the Juno spacecraft. We find, however, that some model types are more plausible than others. In the best three layer models, for example, the transition from molecular to metallic hydrogen needs to be at ~500 GPa while theory and experiments place this transition at ~100 GPa. Four layer models with a single sharp boundary between core and mantle would be short-lived due to rapid convective core erosion. For this reason, we favor our five layer models that include a dilute core surrounded by a stably stratified core transition layer. Six layer models with a small compact core are also possible but with an upper limit of 3 Earth masses for such a compact core. All models assume a 1 bar temperature of 166.1 K, employ physical equations of state, and are constructed with the nonperturbative Concentric Maclaurin Spheroid (CMS) method. We analyze the convergence of this method and describe technical steps that are needed to make this technique so efficient that ensembles of models can be generated., Comment: 11 figures, 1 table, one numerical method to find roots of N dimensional problems

The nuclear two-photon or double-gamma ($2\gamma$) decay is a second-order electromagnetic process whereby a nucleus in an excited state emits two gamma rays simultaneously. To be able to directly measure the $2\gamma$ decay rate in the low-energy regime below the electron-positron pair-creation threshold, we combined the isochronous mode of a storage ring with Schottky resonant cavities. The newly developed technique can be applied to isomers with excitation energies down to $\sim100$\,keV and half-lives as short as $\sim10$\,ms. The half-life for the $2\gamma$ decay of the first-excited $0^+$ state in bare $^{72}\mathrm{Ge}$ ions was determined to be $23.9\left(6\right)$\,ms, which strongly deviates from expectations., Comment: Submitted to Physical Review Letters, 8 pages, 3 figures, 2 tables, 7 equations

In spring 2022, WestEd conducted a literature review to summarize the major frameworks used in career intentions research and the evidence supporting each framework, as well as to develop an initial set of constructs to guide the development of a brief, culturally sensitive computing career intentions survey measuring individual, situational, and societal factors. In summer 2022, WestEd developed a draft computing career intentions survey aligned to seven constructs, and then conducted preliminary validation testing of the survey through a series of cognitive interviews and a small-scale field test with 50 respondents. This technical report is a companion to the 2023 paper presented at the 19th ACM Conference on International Computing Education Research (ICER) (Kao et al., 2023). This technical report contains additional details about the field testing of the survey that did not fit within the page limits of the ICER paper. This report contains the results of two studies: (1) a large-scale field test to more robustly establish the instrument's reliability and test for differential item functioning (DIF), and (2) a test of the survey's test--retest reliability with a subsample of participants from the largescale field test.

Decentralized autonomous organizations (DAOs) are a new, rapidly-growing class of organizations governed by smart contracts. Here we describe how researchers can contribute to the emerging science of DAOs and other digitally-constituted organizations. From granular privacy primitives to mechanism designs to model laws, we identify high-impact problems in the DAO ecosystem where existing gaps might be tackled through a new data set or by applying tools and ideas from existing research fields such as political science, computer science, economics, law, and organizational science. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the wider research community to join the global effort to invent the next generation of organizations., Comment: includes major coordination problems

In this article we consider the iterative solution of the linear system of equations arising from the discretisation of the poly-energetic linear Boltzmann transport equation using a discontinuous Galerkin finite element approximation in space, angle, and energy. In particular, we develop preconditioned Richardson iterations which may be understood as generalisations of source iteration in the mono-energetic setting, and derive computable a posteriori bounds for the solver error incurred due to inexact linear algebra, measured in a relevant problem-specific norm. We prove that the convergence of the resulting schemes and a posteriori solver error estimates are independent of the discretisation parameters. We also discuss how the poly-energetic Richardson iteration may be employed as a preconditioner for the generalised minimal residual (GMRES) method. Furthermore, we show that standard implementations of GMRES based on minimising the Euclidean norm of the residual vector can be utilized to yield computable a posteriori solver error estimates at each iteration, through judicious selections of left- and right-preconditioners for the original linear system. The effectiveness of poly-energetic source iteration and preconditioned GMRES, as well as their respective a posteriori solver error estimates, is demonstrated through numerical examples arising in the modelling of photon transport., Comment: 27 pages, 8 figures

In this article we consider the application of Euler's homogeneous function theorem together with Stokes' theorem to exactly integrate families of polynomial spaces over general polygonal and polyhedral (polytopic) domains in two- and three-dimensions, respectively. This approach allows for the integrals to be evaluated based on only computing the values of the integrand and its derivatives at the vertices of the polytopic domain, without the need to construct a sub-tessellation of the underlying domain of interest. Here, we present a detailed analysis of the computational complexity of the proposed algorithm and show that this depends on three key factors: the ambient dimension of the underlying polytopic domain; the size of the requested polynomial space to be integrated; and the size of a directed graph related to the polytopic domain. This general approach is then employed to compute the volume integrals arising within the discontinuous Galerkin finite element approximation of the linear transport equation. Numerical experiments are presented which highlight the efficiency of the proposed algorithm when compared to standard quadrature approaches defined on a sub-tessellation of the polytopic elements., Comment: 23 pages, 10 figures

Quantifying the heterogeneity of treatment effect is important for understanding how a commercial product or medical treatment affects different subgroups in a population. Beyond the overall impact reflected parameters like the average treatment effect, the analysis of treatment effect heterogeneity further reveals details on the importance of different covariates and how they lead to different treatment impacts. One relevant parameter that addresses such heterogeneity is the variance of treatment effect across different covariate groups, however the treatment effect is defined. One can also derive variable importance parameters that measure (and rank) how much of treatment effect heterogeneity is explained by a targeted subset of covariates. In this article, we propose a new targeted maximum likelihood estimator for a treatment effect variable importance measure. This estimator is a pure plug-in estimator that consists of two steps: 1) the initial estimation of relevant components to plug in and 2) an iterative updating step to optimize the bias-variance tradeoff. The simulation results show that this TMLE estimator has competitive performance in terms of lower bias and better confidence interval coverage compared to the simple substitution estimator and the estimating equation estimator. The application of this method also demonstrates the advantage of a substitution estimator, which always respects the global constraints on the data distribution and that the estimand is a particular function of the distribution.

The SPARC Toroidal Field Model Coil (TFMC) Program was a three-year effort between 2018 and 2021 that developed novel Rare Earth Yttrium Barium Copper Oxide (REBCO) superconductor technologies and then successfully utilized these technologies to design, build, and test a first-in-class, high-field (~20 T), representative-scale (~3 m) superconducting toroidal field coil. With the principal objective of demonstrating mature, large-scale, REBCO magnets, the project was executed jointly by the MIT Plasma Science and Fusion Center (PSFC) and Commonwealth Fusion Systems (CFS). The TFMC achieved its programmatic goal of experimentally demonstrating a large-scale high-field REBCO magnet, achieving 20.1 T peak field-on-conductor with 40.5 kA of terminal current, 815 kN/m of Lorentz loading on the REBCO stacks, and almost 1 GPa of mechanical stress accommodated by the structural case. Fifteen internal demountable pancake-to-pancake joints operated in the 0.5 to 2.0 nOhm range at 20 K and in magnetic fields up to 12 T. The DC and AC electromagnetic performance of the magnet, predicted by new advances in high-fidelity computational models, was confirmed in two test campaigns while the massively parallel, single-pass, pressure-vessel style coolant scheme capable of large heat removal was validated. The REBCO current lead and feeder system was experimentally qualified up to 50 kA, and the crycooler based cryogenic system provided 600 W of cooling power at 20 K with mass flow rates up to 70 g/s at a maximum design pressure of 20 bar-a for the test campaigns. Finally, the feasibility of using passive, self-protection against a quench in a fusion-scale NI TF coil was experimentally assessed with an intentional open-circuit quench at 31.5 kA terminal current., Comment: 17 pages 9 figures, overview paper and the first of a six-part series of papers covering the TFMC Program

We study a quasimorphism, which we call the Dehn twist coefficient (DTC), from the mapping class group of a surface (with a chosen compact boundary component) that generalizes the well-studied fractional Dehn twist coefficient (FDTC) to surfaces of infinite type. Indeed, for surfaces of finite type the DTC coincides with the FDTC. We provide a characterization of the DTC (and thus also of the FDTC) as the unique homogeneous quasimorphism satisfying certain positivity conditions. The FDTC has image contained in $\mathbb{Q}$. In contrast to this, we find that for some surfaces of infinite type the DTC has image all of $\mathbb{R}$. To see this we provide a new construction of maps with irrational rotation behavior for some surfaces of infinite type with a countable space of ends or even just one end. In fact, we find that the DTC is the right tool to detect irrational rotation behavior, even for surfaces without boundary., Comment: 26 pages, 4 figures, comments welcome!

We study the relationship of zonal gravity coefficients, J_2n, zonal winds, and axial moment of inertia (MoI) by constructing models for the interiors of giant planets. We employ the nonperturbative concentric Maclaurin spheroid (CMS) method to construct both physical (realistic equation of state and barotropes) and abstract (small number of constant-density spheroids) interior models. We find that accurate gravity measurements of Jupiter's and Saturn's J_2, J_4, and J_6 by Juno and Cassini spacecrafts do not uniquely determine the MoI of either planet but do constrain it to better than 1%. Zonal winds (or differential rotation, DR) then emerge as the leading source of uncertainty. For Saturn, they are predicted to decrease the MoI by 0.4% because they reach a depth of ~9000 km while on Jupiter, they appear to reach only ~3000 km. We thus predict DR to affect Jupiter's MoI by only 0.01%, too small by one order of magnitude to be detectable by the Juno spacecraft. We find winds primarily affect the MoI indirectly via the gravity harmonic J_6 while direct contributions are much smaller because the effects of pro- and retrograde winds cancel. DR contributes +6% and -0.8% to Saturn's and Jupiter's J_6 value, respectively. This changes the J_6 contribution that comes from the uniformly rotating bulk of the planet that correlates most strongly with the predicted MoI. With our physical models, we predict Jupiter's MoI to be 0.26393+-0.00001. For Saturn, we predict 0.2181+-0.0002, assuming a rotation period of 10:33:34 h that matches the observed polar radius., Comment: 21 pages, 19 figures, 3 tables

At the FRS Ion Catcher (FRS-IC), projectile and fission fragments are produced at relativistic energies, separated in-flight, energy-bunched, slowed down, and thermalized in the ultra-pure helium gas-filled cryogenic stopping cell (CSC). Thermalized nuclei are extracted from the CSC using a combination of DC and RF electric fields and gas flow. This CSC also serves as the prototype CSC for the Super-FRS, where exotic nuclei will be produced at unprecedented rates making it possible to go towards the extremes of the nuclear chart. Therefore, it is essential to efficiently extract thermalized exotic nuclei from the CSC under high beam rate conditions, in order to use the rare exotic nuclei which come as cocktail beams. The extraction efficiency dependence on the intensity of the impinging beam into the CSC was studied with a primary beam of 238U and its fragments. Tests were done with two different versions of the DC electrode structure inside the cryogenic chamber, the standard 1 m long and a short 0.5 m long DC electrode. In contrast to the rate capability of 10^4 ions/s with the long DC electrode, results show no extraction efficiency loss up to the rate of 2x10^5 ions/s with the new short DC electrode. This order of magnitude increase of the rate capability paves the way for new experiments at the FRS-IC, including exotic nuclei studies with in-cell multi-nucleon transfer reactions. The results further validate the design concept of the CSC for the Super-FRS, which was developed to effectively manage beams of even higher intensities.

Mediation analysis in causal inference typically concentrates on one binary exposure, using deterministic interventions to split the average treatment effect into direct and indirect effects through a single mediator. Yet, real-world exposure scenarios often involve multiple continuous exposures impacting health outcomes through varied mediation pathways, which remain unknown a priori. Addressing this complexity, we introduce NOVAPathways, a methodological framework that identifies exposure-mediation pathways and yields unbiased estimates of direct and indirect effects when intervening on these pathways. By pairing data-adaptive target parameters with stochastic interventions, we offer a semi-parametric approach for estimating causal effects in the context of high-dimensional, continuous, binary, and categorical exposures and mediators. In our proposed cross-validation procedure, we apply sequential semi-parametric regressions to a parameter-generating fold of the data, discovering exposure-mediation pathways. We then use stochastic interventions on these pathways in an estimation fold of the data to construct efficient estimators of natural direct and indirect effects using flexible machine learning techniques. Our estimator proves to be asymptotically linear under conditions necessitating n to the negative quarter consistency of nuisance function estimation. Simulation studies demonstrate the square root n consistency of our estimator when the exposure is quantized, whereas for truly continuous data, approximations in numerical integration prevent square root n consistency. Our NOVAPathways framework, part of the open-source SuperNOVA package in R, makes our proposed methodology for high-dimensional mediation analysis available to researchers, paving the way for the application of modified exposure policies which can delivery more informative statistical results for public policy., Comment: 32 pages, 7 figures, 4 tables

Although randomized controlled trials (RCTs) are a cornerstone of comparative effectiveness, they typically have much smaller sample size than observational studies because of financial and ethical considerations. Therefore there is interest in using plentiful historical data (either observational data or prior trials) to reduce trial sizes. Previous estimators developed for this purpose rely on unrealistic assumptions, without which the added data can bias the treatment effect estimate. Recent work proposed an alternative method (prognostic covariate adjustment) that imposes no additional assumptions and increases efficiency in trial analyses. The idea is to use historical data to learn a prognostic model: a regression of the outcome onto the covariates. The predictions from this model, generated from the RCT subjects' baseline variables, are then used as a covariate in a linear regression analysis of the trial data. In this work, we extend prognostic adjustment to trial analyses with nonparametric efficient estimators, which are more powerful than linear regression. We provide theory that explains why prognostic adjustment improves small-sample point estimation and inference without any possibility of bias. Simulations corroborate the theory: efficient estimators using prognostic adjustment compared to without provides greater power (i.e., smaller standard errors) when the trial is small. Population shifts between historical and trial data attenuate benefits but do not introduce bias. We showcase our estimator using clinical trial data provided by Novo Nordisk A/S that evaluates insulin therapy for individuals with type II diabetes., Comment: 48 pages, 3 figures

Parent-child interaction is critical for child development, yet parents may need guidance in some aspects of their engagement with their children. Current research on educational math robots focuses on child-robot interactions but falls short of including the parents and integrating the critical role they play in children's learning. We explore how educational robots can be designed to facilitate parent-child conversations, focusing on math talk, a predictor of later math ability in children. We prototyped capabilities for a social robot to support math talk via reading and play activities and conducted an exploratory Wizard-of-Oz in-home study for parent-child interactions facilitated by a robot. Our findings yield insights into how parents were inspired by the robot's prompts, their desired interaction styles and methods for the robot, and how they wanted to include the robot in the activities, leading to guidelines for the design of parent-child-robot interaction in educational contexts., Comment: 15 pages, Accepted to IDC'23

This study introduces a nonparametric definition of interaction and provides an approach to both interaction discovery and efficient estimation of this parameter. Using stochastic shift interventions and ensemble machine learning, our approach identifies and quantifies interaction effects through a model-independent target parameter, estimated via targeted maximum likelihood and cross-validation. This method contrasts the expected outcomes of joint interventions with those of individual interventions. Validation through simulation and application to the National Institute of Environmental Health Sciences Mixtures Workshop data demonstrate the efficacy of our method in detecting true interaction directions and its consistency in identifying significant impacts of furan exposure on leukocyte telomere length. Our method, called InterXshift, advances the ability to analyze multi-exposure interactions within high-dimensional data, offering significant methodological improvements to understand complex exposure dynamics in health research. We provide peer-reviewed open-source software that employs or proposed methodology in the InterXshift R package.

Since identifying the gap in the H-R Diagram (HRD) marking the transition between partially and fully convective interiors, a unique type of slowly pulsating M dwarf has been proposed. These unstable M dwarfs provide new laboratories in which to understand how changing interior structures can produce potentially observable activity at the surface. In this work, we report the results of the largest high-resolution spectroscopic H$\alpha$ emission survey to date spanning this transition region, including 480 M dwarfs observed using the CHIRON spectrograph at CTIO/SMARTS 1.5-m. We find that M dwarfs with H$\alpha$ in emission are almost entirely found 0 to 0.5 magnitude above the top edge of the gap in the HRD, whereas effectively no stars in and below the gap show emission. Thus, the top edge of the gap marks a relatively sharp activity transition, and there is no anomalous H$\alpha$ activity for stars in the gap. We also identify a new region at 10.3 $

We introduce an $hp$-version discontinuous Galerkin finite element method (DGFEM) for the linear Boltzmann transport problem. A key feature of this new method is that, while offering arbitrary order convergence rates, it may be implemented in an almost identical form to standard multigroup discrete ordinates methods, meaning that solutions can be computed efficiently with high accuracy and in parallel within existing software. This method provides a unified discretisation of the space, angle, and energy domains of the underlying integro-differential equation and naturally incorporates both local mesh and local polynomial degree variation within each of these computational domains. Moreover, general polytopic elements can be handled by the method, enabling efficient discretisations of problems posed on complicated spatial geometries. We study the stability and $hp$-version a priori error analysis of the proposed method, by deriving suitable $hp$-approximation estimates together with a novel inf-sup bound. Numerical experiments highlighting the performance of the method for both polyenergetic and monoenergetic problems are presented., Comment: 27 pages, 2 figures

We present a review of Saturn's interior structure and thermal evolution, with a particular focus on work in the past 5 years. Data from the Cassini mission, including a precise determination of the gravity field from the Grand Finale orbits, and the still ongoing identification of ring wave features in Saturn's C-ring tied to seismic modes in the planet, have led to dramatic advances in our understanding of Saturn's structure. Models that match the gravity field suggest that differential rotation, as seen in the visible atmosphere, extends down to at least a depth of 10,000 km (1/6$^{\rm th}$ the planet's radius). At greater depths, a variety of different investigations all now point to a deep Saturn rotation rate of 10 hours and 33 minutes. There is very compelling evidence for a central heavy element concentration (``core''), that in most recent models is 12-20 Earth masses. Ring seismology strongly suggests that the core is not entirely compact, but is dilute (mixed in with the overlying H/He), and has a substantial radial extent, perhaps out to around one-half of the planet's radius. A wide range of thermal evolution scenarios can match the planet's current luminosity, with progress on better quantifying the helium rain scenario hampered by Saturn's poorly known atmospheric helium abundance. We discuss the relevance of magnetic field data on understanding the planet's current interior structure. We point towards additional future work that combines seismology and gravity within a framework that includes differential rotation, and the utility of a Saturn entry probe., Comment: Invited review. Accepted for publication in "Saturn: The Grand Finale", K. H. Baines et al., eds., Cambridge University Press. All-new follow-up to previous 2016 (pre-Grand Finale) review chapter here: arXiv:1609.06324

Motion capture through tracking retroreflectors obtains highly accurate pose estimation, which is frequently used in robotics. Unlike commercial motion capture systems, fiducial marker-based tracking methods, such as AprilTags, can perform relative localization without requiring a static camera setup. However, popular pose estimation methods based on fiducial markers have lower localization accuracy than commercial motion capture systems. We propose Mobile MoCap, a system that utilizes inexpensive near-infrared cameras for accurate relative localization even while in motion. We present a retroreflector feature detector that performs 6-DoF (six degrees-of-freedom) tracking and operates with minimal camera exposure times to reduce motion blur. To evaluate the proposed localization technique while in motion, we mount our Mobile MoCap system, as well as an RGB camera to benchmark against fiducial markers, onto a precision-controlled linear rail and servo. The fiducial marker approach employs AprilTags, which are pervasively used for localization in robotics. We evaluate the two systems at varying distances, marker viewing angles, and relative velocities. Across all experimental conditions, our stereo-based Mobile MoCap system obtains higher position and orientation accuracy than the fiducial approach. The code for Mobile MoCap is implemented in ROS 2 and made publicly available at https://github.com/RIVeR-Lab/mobile_mocap.

The Juno mission has provided measurements of Jupiter s gravity field with an outstanding level of accuracy, leading to better constraints on the interior of the planet. Improving our knowledge of the internal structure of Jupiter is key to understanding its formation and evolution but is also important in the framework of exoplanet exploration. In this study, we investigated the differences between the state-of-the-art equations of state and their impact on the properties of interior models. Accounting for uncertainty on the hydrogen and helium equation of state, we assessed the span of the interior features of Jupiter. We carried out an extensive exploration of the parameter space and studied a wide range of interior models using Markov chain Monte Carlo (MCMC) simulations. To consider the uncertainty on the equation of state, we allowed for modifications of the equation of state in our calculations. Our models harbour a dilute core and indicate that Jupiter s internal entropy is higher than what is usually assumed from the Galileo probe measurements. We obtain solutions with extended dilute cores, but contrary to other recent interior models of Jupiter, we also obtain models with small dilute cores. The dilute cores in such solutions extend to 20% of Jupiter s mass, leading to better agreement with formation evolution models. We conclude that the equations of state used in Jupiter models have a crucial effect on the inferred structure and composition. Further explorations of the behaviour of hydrogen helium mixtures at the pressure and temperature conditions in Jupiter will help to constrain the interior of the planet, and therefore its origin.

Traditional regulations of chemical exposure tend to focus on single exposures, overlooking the potential amplified toxicity due to multiple concurrent exposures. We are interested in understanding the average outcome if exposures were limited to fall under a multivariate threshold. Because threshold levels are often unknown a priori, we provide an algorithm that finds exposure threshold levels where the expected outcome is maximized or minimized. Because both identifying thresholds and estimating policy effects on the same data would lead to overfitting bias, we also provide a data-adaptive estimation framework, which allows for both threshold discovery and policy estimation. Simulation studies show asymptotic convergence to the optimal exposure region and to the true effect of an intervention. We demonstrate how our method identifies true interactions in a public synthetic mixture data set. Finally, we applied our method to NHANES data to discover metal exposures that have the most harmful effects on telomere length. We provide an implementation in the CVtreeMLE R package.

The flight of the Micro-X sounding rocket on July 22, 2018 marked the first operation of Transition-Edge Sensors and their SQUID readouts in space. The instrument combines the microcalorimeter array with an imaging mirror to take high-resolution spectra from extended X-ray sources. The first flight target was the Cassiopeia~A Supernova Remnant. While a rocket pointing malfunction led to no time on-target, data from the flight was used to evaluate the performance of the instrument and demonstrate the flight viability of the payload. The instrument successfully achieved a stable cryogenic environment, executed all flight operations, and observed X-rays from the on-board calibration source. The flight environment did not significantly affect the performance of the detectors compared to ground operation. The flight provided an invaluable test of the impact of external magnetic fields and the instrument configuration on detector performance. This flight provides a milestone in the flight readiness of these detector and readout technologies, both of which have been selected for future X-ray observatories.

Optimization equips engineers and scientists in a variety of fields with the ability to transcribe their problems into a generic formulation and receive optimal solutions with relative ease. Industries ranging from aerospace to robotics continue to benefit from advancements in optimization theory and the associated algorithmic developments. Nowadays, optimization is used in real time on autonomous systems acting in safety critical situations, such as self-driving vehicles. It has become increasingly more important to produce robust solutions by incorporating uncertainty into optimization programs. This paper provides a short survey about the state of the art in optimization under uncertainty. The paper begins with a brief overview of the main classes of optimization without uncertainty. The rest of the paper focuses on the different methods for handling both aleatoric and epistemic uncertainty. Many of the applications discussed in this paper are within the domain of control. The goal of this survey paper is to briefly touch upon the state of the art in a variety of different methods and refer the reader to other literature for more in-depth treatments of the topics discussed here., Comment: 13 pages

We present a velocity-based moving mesh virtual element method for the numerical solution of PDEs involving moving boundaries. The virtual element method is used for computing both the mesh velocity and a conservative Arbitrary Lagrangian-Eulerian solution transfer on general polygonal meshes. The approach extends the linear finite element method to polygonal mesh structures, achieving the same degree of accuracy. In the context of moving meshes, a major advantage of the virtual element approach is the ease with which nodes can be inserted on mesh edges. Demonstrations of node insertion techniques are presented to show that moving polygonal meshes can be simply adapted for situations where a boundary encounters a solid object or another moving boundary, without reduction in degree of accuracy.

Distributed acoustic sensing (DAS) is a relatively new technology for recording stress wave propagation, with promising applications in both engineering and geophysics. DAS's ability to simultaneously collect high spatial resolution data over long arrays suggests that it is especially well suited for near-surface imaging applications such as 2D MASW (multi-channel analysis of surface waves). 2D MASW aims to produce a pseudo-2D cross-section of shear-wave velocity (Vs) for the purpose of identifying and characterizing subsurface layering and anomalies. These cross-sections are produced by interpolating numerous 1D Vs profiles extracted from overlapping sub-arrays along the testing alignment. When using traditional seismic equipment, these sub-arrays are typically collected in a roll-along configuration, where the equipment is moved along the alignment at some predetermined sub-array interval. DAS does not have the same limitations, as data from all shot locations are simultaneously recorded along the entire length of the DAS array. This alleviates the requirements to pre-determine sub-array length and interval during the acquisition stage and allows for multiple geometries to be investigated during the processing stage. The present study utilizes DAS data to evaluate the effects of sub-array length on 2D MASW results at a well-characterized field test site. We organize the DAS waveforms into multiple sets of overlapping MASW sub-arrays of differing lengths, allowing for direct comparison of the derived results at the same site. We show that the length of the individual MASW sub-arrays has a significant effect on the resolution of the resulting cross-sections as well as the resolved location of large impedance contrasts at our study site and evaluate those locations compared to invasive testing., Comment: 32 pages, 12 figures

As part of a comprehensive effort to characterize the nearest stars, the CHIRON echelle spectrograph on the CTIO/SMARTS 1.5m telescope is being used to acquire high resolution (R = 80000) spectra of K dwarfs within 50 parsecs. This paper provides spectral details about 35 K dwarfs from five benchmark sets with estimated ages spanning 20 Myr -- 5.7 Gyr. Four spectral age and activity indicators are tested, three of which aligned with the estimated ages of the benchmark groups -- the Na I doublet (5889.95 $\r{A}$ and 5895.92 $\r{A}$), the H$\alpha$ line (6562.8 $\r{A}$), and the Li I resonance line (6707.8 $\r{A}$). The benchmark stars are then used to evaluate seven field K dwarfs exhibiting variable radial velocities for which initial CHIRON data did not show obvious companions. Two of these stars are estimated to be younger than 700 Myr, while one exhibits stellar activity unusual for older K dwarf field stars and is possibly young. The four remaining stars turn out to be spectroscopic binaries, two of which are being reported here for the first time with orbital periods found using CHIRON data. Spectral analysis of the combined sample of 42 benchmark and variable radial velocity stars indicates temperatures ranging from 3900--5300 K and metallicities from $-$0.4 $<$ [Fe/H] $<$ $+$0.2. We also determine $log g$ = 4.5--4.7 for main sequence K dwarfs. Ultimately, this study will target several thousand of the nearest K dwarfs, and provide results that will serve present and future studies of stellar astrophysics and exoplanet habitability., Comment: 20 pages, 11 figures, 4 tables, accepted to AJ

We present the visual orbits of four spectroscopic binary stars, HD 61859, HD 89822, HD 109510, and HD 191692, using long baseline interferometry with the CHARA Array. We also obtained new radial velocities from echelle spectra using the APO 3.5 m, CTIO 1.5 m, and Fairborn Observatory 2.0 m telescopes. By combining the astrometric and spectroscopic observations, we solve for the full, three-dimensional orbits and determine the stellar masses to 1-12% uncertainty and distances to 0.4-6% uncertainty. We then estimate the effective temperature and radius of each component star through Doppler tomography and spectral energy distribution analyses. We found masses of 1.4-3.5 Msun, radii of 1.5-4.7 Rsun, and temperatures of 6400-10300K. We then compare the observed stellar parameters to the predictions of the stellar evolution models, but found that only one of our systems fits well with the evolutionary models., Comment: Accepted for publication in AJ. arXiv admin note: text overlap with arXiv:2005.00546

Due to the Covid-19 pandemic in 2020 or other business decisions, remote work is becoming increasingly popular. "Remote first" working environments exist within companies where most employees work remotely. This paper takes a deep dive into the remote-first mentality. It investigates its effects on employees at varying stages in their careers, day-to-day productivity, and working relationships with team members. We found that the remote-first mentality most impacts seasoned employees and managers, potentially due to trouble adjusting to a new way of working compared to the rest of their careers and the "always on" mentality associated with working from home. Regarding productivity, we found that while software development productivity appears unimpacted, the effectiveness of communication and employee wellbeing saw declines which are generally associated with lowered productivity. Finally, we looked closer at the communication side of things and how remote work impacts relationship building. We found that the most significant impacts on relationship building centered around "trust" and "credibility" being harder to build due to a lack of non-verbal cues during social interactions.

While Jupiter's massive gas envelope consists mainly of hydrogen and helium, the key to understanding Jupiter's formation and evolution lies in the distribution of the remaining (heavy) elements. Before the Juno mission, the lack of high-precision gravity harmonics precluded the use of statistical analyses in a robust determination of the heavy-elements distribution in Jupiter's envelope. In this paper, we assemble the most comprehensive and diverse collection of Jupiter interior models to date and use it to study the distribution of heavy elements in the planet's envelope. We apply a Bayesian statistical approach to our interior model calculations, reproducing the Juno gravitational and atmospheric measurements and constraints from the deep zonal flows. Our results show that the gravity constraints lead to a deep entropy of Jupiter corresponding to a 1 bar temperature 5-15 K higher than traditionally assumed. We also find that uncertainties in the equation of state are crucial when determining the amount of heavy elements in Jupiter's interior. Our models put an upper limit to the inner compact core of Jupiter of 7 Earth masses, independently on the structure model (with or without dilute core) and the equation of state considered. Furthermore, we robustly demonstrate that Jupiter's envelope is inhomogenous, with a heavy-element enrichment in the interior relative to the outer envelope. This implies that heavy element enrichment continued through the gas accretion phase, with important implications for the formation of giant planets in our solar system and beyond., Comment: Accepted for publication in A&A

The Juno mission has revolutionized and challenged our understanding of Jupiter. As Juno transitioned to its extended mission, we review the major findings of Jupiter's internal structure relevant to understanding Jupiter's formation and evolution. Results from Juno's investigation of Jupiter's interior structure imply that the planet has compositional gradients and is accordingly non-adiabatic, with a complex internal structure. These new results imply that current models of Jupiter's formation and evolution require a revision. In this paper, we discuss potential formation and evolution paths that can lead to an internal structure model consistent with Juno data, and the constraints they provide. We note that standard core accretion formation models, including the heavy-element enrichment during planetary growth is consistent with an interior that is inhomogeneous with composition gradients in its deep interior. However, such formation models typically predict that this region, which could be interpreted as a primordial dilute core, is confined to about 10% of Jupiter's total mass. In contrast, structure models that fit Juno data imply that this region contains 30% of the mass or more. One way to explain the origin of this extended region is by invoking a relatively long (about 2 Myrs) formation phase where the growing planet accretes gas and planetesimals delaying the runaway gas accretion. Alternatively, Jupiter's fuzzy core could be a result of a giant impact or convection post-formation. These novel scenarios require somewhat special and specific conditions. Clarity on the plausibility of such conditions could come from future high-resolution observations of planet-forming regions around other stars, from the observed and modeled architectures of extrasolar systems with giant planets, and future Juno data obtained during its extended mission., Comment: invited review for Icarus, accepted for publication

We rigorously assess the potential for extracting high-resolution, multi-mode surface wave dispersion data from distributed acoustic sensing (DAS) measurements using active-source multichannel analysis of surface waves (MASW). We have utilized both highly-controlled, broadband vibroseis shaker trucks and more-variable, narrow-band sledgehammer sources to excite the near surface, and compare the DAS-derived dispersion data obtained from both source types directly with concurrently acquired traditional geophone-derived dispersion data. We find that the differences between the two sensing approaches are minimal and well within the dispersion uncertainty bounds associated with each individual measurement type when the following conditions are met for DAS: (a) a tight-buffered or strain-sensing fiber-optic cable is used, (b) the cable is buried in a shallow trench to enhance coupling, and (c) short gauge lengths and small channel separations are used. We also show that frequency-dependent normalization of the dispersion image following MASW processing removes the effects of scaling, integration, and differentiation on the measured waveforms, thereby allowing nearly identical dispersion data to be extracted from geophone waveforms and DAS waveforms without requiring them to first be converted into equivalent units. We demonstrate that the short wavelength DAS dispersion measurements are limited by both the gauge length and the more commonly considered channel separation. We further show that it is possible to extract essentially equivalent surface wave dispersion data from seismic measurements made using a traditional geophone array or two different DAS cables. Finally, we show that shear wave velocity profiles recovered from the DAS data using an uncertainty-consistent, multi-mode inversion agree favorably with cone penetration tests performed at the site., Comment: 22 pages, 12 figures

Districts providing strong centralized COVID-19 responses approached the crisis from a top-down leadership and guidance model which constrained school flexibility to act outside of the district's direction. This is one of a series of briefs that focused on a 'critical incident' surrounding school closure and offers pragmatic suggestions to educational leaders as they continue to grapple with the disruptions of the pandemic.

The Wide Field Imager (WFI) flying on Athena will usher in the next era of studying the hot and energetic Universe. WFI observations of faint, diffuse sources will be limited by uncertainty in the background produced by high-energy particles. These particles produce easily identified "cosmic-ray tracks" along with signals from secondary photons and electrons generated by particle interactions with the instrument. The signal from these secondaries is identical to the X-rays focused by the optics, and cannot be filtered without also eliminating these precious photons. As part of a larger effort to understand the WFI background, we here present results from a study of background-reduction techniques that exploit the spatial correlation between cosmic-ray particle tracks and secondary events. We use Geant4 simulations to generate a realistic particle background, sort this into simulated WFI frames, and process those frames in a similar way to the expected flight and ground software to produce a WFI observation containing only particle background. The technique under study, Self Anti-Coincidence or SAC, then selectively filters regions of the detector around particle tracks, turning the WFI into its own anti-coincidence detector. We show that SAC is effective at improving the systematic uncertainty for observations of faint, diffuse sources, but at the cost of statistical uncertainty due to a reduction in signal. If sufficient pixel pulse-height information is telemetered to the ground for each frame, then this technique can be applied selectively based on the science goals, providing flexibility without affecting the data quality for other science. The results presented here are relevant for any future silicon-based pixelated X-ray imaging detector, and could allow the WFI and similar instruments to probe to truly faint X-ray surface brightness., Comment: 38 pages, 27 figures. Accepted for publication in JATIS. arXiv admin note: text overlap with arXiv:2012.01347

A stellar occultation by Neptune's main satellite, Triton, was observed on 5 October 2017 from Europe, North Africa, and the USA. We derived 90 light curves from this event, 42 of which yielded a central flash detection. We aimed at constraining Triton's atmospheric structure and the seasonal variations of its atmospheric pressure since the Voyager 2 epoch (1989). We also derived the shape of the lower atmosphere from central flash analysis. We used Abel inversions and direct ray-tracing code to provide the density, pressure, and temperature profiles in the altitude range $\sim$8 km to $\sim$190 km, corresponding to pressure levels from 9 {\mu}bar down to a few nanobars. Results. (i) A pressure of 1.18$\pm$0.03 {\mu}bar is found at a reference radius of 1400 km (47 km altitude). (ii) A new analysis of the Voyager 2 radio science occultation shows that this is consistent with an extrapolation of pressure down to the surface pressure obtained in 1989. (iii) A survey of occultations obtained between 1989 and 2017 suggests that an enhancement in surface pressure as reported during the 1990s might be real, but debatable, due to very few high S/N light curves and data accessible for reanalysis. The volatile transport model analysed supports a moderate increase in surface pressure, with a maximum value around 2005-2015 no higher than 23 {\mu}bar. The pressures observed in 1995-1997 and 2017 appear mutually inconsistent with the volatile transport model presented here. (iv) The central flash structure does not show evidence of an atmospheric distortion. We find an upper limit of 0.0011 for the apparent oblateness of the atmosphere near the 8 km altitude., Comment: 52 pages, 26 figures in the main paper, 2 figures in appendix B, 9 figures in appendix C, 1 long table over 5 pages

It is shown that the Poincar\'e-Birkhoff fixed point theorem may be proven by extending the geometric approach originally devised by Henri Poincar\'e himself, along with several results from elementary differential topology. Beginning with an example application of the theorem, we proceed by systematically constructing and classifying a certain set of invariant curves and their critical points. This classification is then used to prove the correctness of a procedure which guarantees the existence of at least two fixed points for any twist map of the annulus admitting a positive integral invariant., Comment: 34 pages, 16 figures. Originally published by PUCP Pro Mathematica, Vol. 31 No. 62 (2021)

Micro-X is an X-ray sounding rocket payload that had its first flight on July 22, 2018. The goals of the first flight were to operate a transition edge sensor (TES) X-ray microcalorimeter array in space and take a high-resolution spectrum of the Cassiopeia A supernova remnant. The first flight was considered a partial success. The array and its time-division multiplexing readout system were successfully operated in space, but due to a failure in the attitude control system, no time on-target was acquired. A re-flight has been scheduled for summer 2022. Since the first flight, modifications have been made to the detector systems to improve noise and reduce the susceptibility to magnetic fields. The three-stage SQUID circuit, NIST MUX06a, has been replaced by a two-stage SQUID circuit, NIST MUX18b. The initial laboratory results for the new detector system will be presented in this paper., Comment: LTD proceedings, 6 pages, 3 figures, 1 table