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Research on ultra-high dose rate (UHDR) radiation therapy has indicated its potential to spare normal tissue while maintaining equivalent tumor control compared to conventional treatments. First clinical trials are underway. The randomized phase II/III FEATHER clinical trial at the Paul Scherrer Institute in collaboration with the University of Zurich Animal Hospital is one of the first curative domestic animal trials to be attempted, and it is designed to provide a good example for human trials. However, the lack of standardized quality assurance (QA) guidelines for FLASH clinical trials presents a significant challenge in trial design. This work aims to demonstrate the development and testing of QA and reporting procedures implemented in the FEATHER clinical trial. We have expanded the clinical QA program to include UHDR-specific QA and additional patient-specific QA. Furthermore, we have modified the monitor readout to enable time-resolved measurements, allowing delivery log files to be used for dose and dose rate recalculations. Finally, we developed a reporting strategy encompassing relevant parameters for retrospective studies. We evaluated our QA and reporting procedures with simulated treatments. This testing confirmed that our QA procedures effectively ensure the correct and safe delivery of the planned dose. Additionally, we demonstrated that we could reconstruct the delivered dose and dose rate using the delivery log files. We developed and used in practice a comprehensive QA and reporting protocol for a FLASH clinical trial at the Paul Scherrer Institute. This work aims to establish guidelines and standardize reporting practices for future advancements in the FLASH-RT field., Comment: 7 figures

The FLASH effect refers to a lower normal tissue damage for an equivalent tumour response, potentially widening the therapeutic window for radiotherapy. Although this effect has been demonstrated in various experiments using different types of particles and irradiation parameters, the underlying mechanism is not yet clearly understood. Uncertainties surround the conducted experiments, the explored parameter space, and the variability of reported results. To gain a better overview, we created a dataset that includes in-vivo FLASH experiments. This dataset documents all machine and biological dosimetric parameters, and for determined endpoints, it includes the outcome of the experiment. Our goal is to increase awareness of the results and their variability and provide a useful research and analysis tool for the community. The database contains peer-reviewed papers published until March 2024 on the FLASH in-vivo (murine) experiments. From each paper, previously defined parameters have been manually extracted and/or recalculated to ensure compatibility within the database entries. We provide two types of datasets: a user-friendly web-based Notion database and spreadsheets on a Zenodo repository. The database contains all the reviewed papers with extracted information in text or numeric form. Users can duplicate the database or view, search, filter, and reorganise online entries. The spreadsheets contain the data for the most analysed endpoints, allowing a comparative analysis. The study has two main applications. The web-based database will allow for a user-friendly search of information and meta-data of all published FLASH murine data. This will facilitate future research efforts to better understand the FLASH effect. The spreadsheets are a simple and useful tool for the community to conduct statistical analysis and determine the parameters associated with the FLASH effect., Comment: Medical Physics dataset article, 3 figures and 2 tables

Purpose: Beam angle selection is critical in proton therapy treatment planning, yet automated approaches remain underexplored. This study presents and evaluates GAMBAS, a novel, fast machine learning model for automatic beam angle selection. Methods: The model extracts a predefined set of anatomical features from a patient's CT and structure contours. Using these features, it identifies the most similar patient from a training database and suggests that patient's beam arrangement. A retrospective study with 19 patients was conducted, comparing this model's suggestions to human planners' choices and randomly selected beam arrangements from the training dataset. An expert treatment planner evaluated the plans on quality (scale 1-5), ranked them, and guessed the method used. Results: The number of acceptable (score 4 or 5) plans was comparable between human-chosen 17 (89%) and model-selected 16(84%) beam arrangements. The fully automatic treatment planning took between 4 - 7 min (mean 5 min). Conclusion: The model produces beam arrangements of comparable quality to those chosen by human planners, demonstrating its potential as a fast tool for quality assurance and patient selection, although it is not yet ready for clinical use., Comment: 8 pages, 2 figures, 1 table

The importance of computers is continually increasing in radiotherapy. Efficient algorithms, implementations and the ability to leverage advancements in computer science are crucial to improve cancer care even further and deliver the best treatment to each patient. Yet, the software landscape for radiotherapy is fragmented into proprietary systems that do not share a common interface. Further, the radiotherapy community does not have access to the vast possibilities offered by modern programming languages and their ecosystem of libraries yet. We present JulianA.jl, a novel Julia package for radiotherapy. It aims to provide a modular and flexible foundation for the development and efficient implementation of algorithms and workflows for radiotherapy researchers and clinicians. JulianA.jl can be interfaced with any scriptable treatment planning system, be it commercial, open source or in-house developed. This article highlights our design choices and showcases the package's simplicity and powerful automatic treatment planning capabilities.

Background: Automatic treatment planning promises many benefits for both research and clinical environments. For clinics, autoplanning promises to reduce planning time and achieve more comparable treatment plans and thereby reduce inter-planner variability. Further, it can assist clinicians in quality assurance by providing a minimum plan quality standard. Finally, autoplanning is an essential part of patient selection, which is crucial for the advancement of proton therapy itself. Methods: A retrospective planning study using a cohort of 17 head-and-neck cancer patients treated at our institute. The clinically accepted plans created by dosimetrists (d-plans) were compared to automatically generated JulianA plans (j-plans). Both methods used the same beam arrangement. The plans were analysed by two expert reviewers without knowing how each plan was created. They assessed the plan quality and stated a preference. Results: All of the j-plans were deemed rather or clearly acceptable, resulting in a higher acceptability than the d-plans. The j-plan was considered superior in 14 (82.4%) cases, of equal quality for 1 (5.9%) and inferior to the d-plan for only 2 (11.8%) of the cases. The reviewers concluded that JulianA achieves more conformal dose distributions for the 15 (88.2%) cases where the j-plans were at least as good as the d-plans. Conclusions: The results show that the JulianA is ready to be used as a clinical quality assurance tool and research platform at our institute. While these results are encouraging, further research is needed to reduce the number of spots further and introduce robustness considerations into the optimisation algorithm in order to employ it on a daily basis for patient treatment.

Motion information from 4D medical imaging offers critical insights into dynamic changes in patient anatomy for clinical assessments and radiotherapy planning and, thereby, enhances the capabilities of 3D image analysis. However, inherent physical and technical constraints of imaging hardware often necessitate a compromise between temporal resolution and image quality. Frame interpolation emerges as a pivotal solution to this challenge. Previous methods often suffer from discretion when they estimate the intermediate motion and execute the forward warping. In this study, we draw inspiration from fluid mechanics to propose a novel approach for continuously modeling patient anatomic motion using implicit neural representation. It ensures both spatial and temporal continuity, effectively bridging Eulerian and Lagrangian specifications together to naturally facilitate continuous frame interpolation. Our experiments across multiple datasets underscore the method's superior accuracy and speed. Furthermore, as a case-specific optimization (training-free) approach, it circumvents the need for extensive datasets and addresses model generalization issues.

Background and purpose: Deformable image registration (DIR) is a crucial tool in radiotherapy for extracting and modelling organ motion. However, when significant changes and sliding boundaries are present, it faces compromised accuracy and uncertainty, determining the subsequential contour propagation and dose accumulation procedures. Materials and methods: We propose an implicit neural representation (INR)-based approach modelling motion continuously in both space and time, named Continues-sPatial-Temporal DIR (CPT-DIR). This method uses a multilayer perception (MLP) network to map 3D coordinate (x,y,z) to its corresponding velocity vector (vx,vy,vz). The displacement vectors (dx,dy,dz) are then calculated by integrating velocity vectors over time. The MLP's parameters can rapidly adapt to new cases without pre-training, enhancing optimisation. The DIR's performance was tested on the DIR-Lab dataset of 10 lung 4DCT cases, using metrics of landmark accuracy (TRE), contour conformity (Dice) and image similarity (MAE). Results: The proposed CPT-DIR can reduce landmark TRE from 2.79mm to 0.99mm, outperforming B-splines' results for all cases. The MAE of the whole-body region improves from 35.46HU to 28.99HU. Furthermore, CPT-DIR surpasses B-splines for accuracy in the sliding boundary region, lowering MAE and increasing Dice coefficients for the ribcage from 65.65HU and 90.41% to 42.04HU and 90.56%, versus 75.40HU and 89.30% without registration. Meanwhile, CPT-DIR offers significant speed advantages, completing in under 15 seconds compared to a few minutes with the conventional B-splines method. Conclusion: Leveraging the continuous representations, the CPT-DIR method significantly enhances registration accuracy, automation and speed, outperforming traditional B-splines in landmark and contour precision, particularly in the challenging areas.

In recent advancements in proton therapy, MR-based treatment planning is gaining momentum to minimize additional radiation exposure compared to traditional CT-based methods. This transition highlights the critical need for accurate MR-to-CT image synthesis, which is essential for precise proton dose calculations. Our research introduces the Diffusion Schr\"odinger Bridge Models (DSBM), an innovative approach for high-quality MR-to-CT synthesis. DSBM learns the nonlinear diffusion processes between MR and CT data distributions. This method improves upon traditional diffusion models by initiating synthesis from the prior distribution rather than the Gaussian distribution, enhancing both generation quality and efficiency. We validated the effectiveness of DSBM on a head and neck cancer dataset, demonstrating its superiority over traditional image synthesis methods through both image-level and dosimetric-level evaluations. The effectiveness of DSBM in MR-based proton treatment planning highlights its potential as a valuable tool in various clinical scenarios., Comment: International Conference on the use of Computers in Radiation therapy (ICCR)

Most earthquake energy release arises during fault slip many kilometers below the Earth's surface. Understanding earthquakes and their hazard requires mapping the geometry and distribution of this slip. Such finite-fault maps are typically derived from surface phenomena, such as seismic and geodetic ground motions. Here we introduce an imaging procedure for mapping finite-fault slip directly from seismicity and aftershocks - phenomena occurring at depth around an earthquake rupture. For specified source and receiver faults, we map source-fault slip in 3D by correlation of point-source Coulomb failure stress change (${\Delta}$CFS) kernels across the distribution of seismicity around an earthquake. These seismicity-stress maps show relative, static fault slip compatible with the surrounding seismicity given the physics of ${\Delta}$CFS; they can aid other slip inversions and aftershock forecasting, and be obtained for early instrumental earthquakes. We verify this procedure recovers synthetic fault slip, and matches independent estimates of slip for the 2004 Mw 6.0 Parkfield and 2021 Mw 6.0 Antelope Valley California earthquakes. For the 2018 Mw 7.1 Anchorage Alaska intra-slab earthquake, seismicity-stress maps, combined with multi-scale precise hypocenter relocation, resolve the enigma of which mainshock faulting plane ruptured (the gently east-dipping plane), and clarify slab structures activated in the energetic aftershock sequence., Comment: 41 pages, 12 figures; for supplementary movies, see https://zenodo.org/doi/10.5281/zenodo.10939981 ; presented at 2024 Annual Meeting, Seismological Society of America, 29 April-3 May, Anchorage, Alaska. v2: updated synthetic fault slip analysis, minor text changes

This appendix volume supplements "Evaluating the Federal Innovative Assessment Demonstration Authority: Early Implementation and Progress of State Efforts to Develop New Statewide Academic Assessments. Evaluation Report. NCEE 2023-004" analyzing the early progress of the first five assessment systems participating in the Innovative Assessment Demonstration Authority (IADA) created by the 2015 reauthorization of the Elementary and Secondary Education Act. These systems include: (1) the New Hampshire Performance Assessment of Competency Education (NH PACE); (2) the Louisiana Educational Assessment Program 2025 Humanities (LEAP 2025 Humanities); (3) the North Carolina Personalized Assessment Tool (NC PAT); (4) the Georgia MAP Assessment Partnership (GMAP) through-year assessment and (5) the Georgia Navvy assessment system. The volume documents the features of the IADA program and the five IADA systems, the study team's research activities, and includes more detailed findings than were summarized in the report. [For the full report, see ED627872. For the Study Highlights, see ED627880.]

Education officials have long hoped that the statewide academic assessments most students take each year could be used not only for accountability but also to guide instruction. Congress established the Innovative Assessment Demonstration Authority (IADA) program in 2015 to help address this goal, offering up to seven states temporary flexibility from federal testing requirements so that they may more easily make progress toward replacing their current assessments with more innovative ones. The key incentive to participate in IADA is that students trying out the innovative assessment are not required to also take the state's current assessment. However, states approved for IADA must still show that their innovative assessments meet most requirements for federal accountability, and they are expected to implement the new assessments statewide within 5 years. This report describes the progress of the first five assessment systems approved under IADA in order to help policymakers consider expanding the program to more states. The report is primarily based on an analysis of states' IADA applications and performance reports to the U.S. Department of Education through the 2020-2021 school year and is part of a broader evaluation of IADA required by Congress. [For the Appendix, see ED627873. For the Study Highlights, see ED627880.]

Intra-fraction motion in radiotherapy is commonly modeled using deformable image registration (DIR). However, existing methods often struggle to balance speed and accuracy, limiting their applicability in clinical scenarios. This study introduces a novel approach that harnesses Neural Graphics Primitives (NGP) to optimize the displacement vector field (DVF). Our method leverages learned primitives, processed as splats, and interpolates within space using a shallow neural network. Uniquely, it enables self-supervised optimization at an ultra-fast speed, negating the need for pre-training on extensive datasets and allowing seamless adaptation to new cases. We validated this approach on the 4D-CT lung dataset DIR-lab, achieving a target registration error (TRE) of 1.15\pm1.15 mm within a remarkable time of 1.77 seconds. Notably, our method also addresses the sliding boundary problem, a common challenge in conventional DIR methods.

Background: In MR-guided proton therapy planning, aligning MR and CT images is key for MR-based CT synthesis, especially in mobile regions like the head-and-neck. Misalignments here can lead to less accurate synthetic CT (sCT) images, impacting treatment precision. Purpose: This study introduces a novel network that cohesively unifies image generation and registration processes to enhance the quality and anatomical fidelity of sCTs derived from better-aligned MR images. Methods: The approach synergizes a generation network (G) with a deformable registration network (R), optimizing them jointly in MR-to-CT synthesis. This goal is achieved by alternately minimizing the discrepancies between the generated/registered CT images and their corresponding reference CT counterparts. The generation network employs a UNet architecture, while the registration network leverages an implicit neural representation of the Deformable Vector Fields (DVFs). We validated this method on a dataset comprising 60 Head-and-Neck patients, reserving 12 cases for holdout testing. Results: Compared to the baseline Pix2Pix method with MAE 124.95\pm 30.74 HU, the proposed technique demonstrated 80.98\pm 7.55 HU. The unified translation-registration network produced sharper and more anatomically congruent outputs, showing superior efficacy in converting MR images to sCTs. Additionally, from a dosimetric perspective, the plan recalculated on the resulting sCTs resulted in a remarkably reduced discrepancy to the reference proton plans. Conclusions: This study conclusively demonstrates that a holistic MR-based CT synthesis approach, integrating both image-to-image translation and deformable registration, significantly improves the precision and quality of sCT generation, particularly for the challenging body area with varied anatomic changes between corresponding MR and CT.

Creating high quality treatment plans is crucial for a successful radiotherapy treatment. However, it demands substantial effort and special training for dosimetrists. Existing automated treatment planning systems typically require either an explicit prioritization of planning objectives, human-assigned objective weights, large amounts of historic plans to train an artificial intelligence or long planning times. Many of the existing auto-planning tools are difficult to extend to new planning goals. A new spot weight optimisation algorithm, called JulianA, was developed. The algorithm minimises a scalar loss function that is built only based on the prescribed dose to the tumour and organs at risk (OARs), but does not rely on historic plans. The objective weights in the loss function have default values that do not need to be changed for the patients in our dataset. The system is a versatile tool for researchers and clinicians without specialised programming skills. Extending it is as easy as adding an additional term to the loss function. JulianA was validated on a dataset of 19 patients with intra- and extracerebral neoplasms within the cranial region that had been treated at our institute. For each patient, a reference plan which was delivered to the cancer patient, was exported from our treatment database. Then JulianA created the auto plan using the same beam arrangement. The reference and auto plans were given to a blinded independent reviewer who assessed the acceptability of each plan, ranked the plans and assigned the human-/machine-made labels. The auto plans were considered acceptable in 16 out of 19 patients and at least as good as the reference plan for 11 patients. Whether a plan was crafted by a dosimetrist or JulianA was only recognised for 9 cases. The median time for the spot weight optimisation is approx. 2 min (range: 0.5 min - 7 min).

We present light curves and flares from a seven day, multi-wavelength observational campaign of AU Mic, a young and active dM1e star with exoplanets and a debris disk. We report on 73 unique flares between the X-ray to optical data. We use high-time resolution NUV photometry and soft X-ray (SXR) data from XMM-Newton to study the empirical Neupert effect, which correlates the gradual and impulsive phase flaring emissions. We find that 65% (30 of 46) flares do not follow the Neupert effect, which is three times more excursions than seen in solar flares, and propose a four part Neupert effect classification (Neupert, Quasi-Neupert, Non-Neupert I & II) to explain the multi-wavelength responses. While the SXR emission generally lags behind the NUV as expected from the chromospheric evaporation flare models, the Neupert effect is more prevalent in larger, more impulsive flares. Preliminary flaring rate analysis with X-ray and U-band data suggests that previously estimated energy ratios hold for a collection of flares observed over the same time period, but not necessarily for an individual, multi-wavelength flare. These results imply that one model cannot explain all stellar flares and care should be taken when extrapolating between wavelength regimes. Future work will expand wavelength coverage using radio data to constrain the nonthermal empirical and theoretical Neupert effects to better refine models and bridge the gap between stellar and solar flare physics., Comment: 46 pages, 18 figures, 15 tables. Accepted for publication in The Astrophysical Journal

Objective: The aim of this work is to investigate the feasibility of the Jagiellonian Positron Emission Tomography (J-PET) scanner for intra-treatment proton beam range monitoring. Approach: The Monte Carlo simulation studies with GATE and PET image reconstruction with CASToR were performed in order to compare six J-PET scanner geometries (three dual-heads and three cylindrical). We simulated proton irradiation of a PMMA phantom with a Single Pencil Beam (SPB) and Spread-Out Bragg Peak (SOBP) of various ranges. The sensitivity and precision of each scanner were calculated, and considering the setup's cost-effectiveness, we indicated potentially optimal geometries for the J-PET scanner prototype dedicated to the proton beam range assessment. Main results: The investigations indicate that the double-layer cylindrical and triple-layer double-head configurations are the most promising for clinical application. We found that the scanner sensitivity is of the order of 10$^{-5}$ coincidences per primary proton, while the precision of the range assessment for both SPB and SOBP irradiation plans was found below 1 mm. Among the scanners with the same number of detector modules, the best results are found for the triple-layer dual-head geometry. Significance: We performed simulation studies demonstrating that the feasibility of the J-PET detector for PET-based proton beam therapy range monitoring is possible with reasonable sensitivity and precision enabling its pre-clinical tests in the clinical proton therapy environment. Considering the sensitivity, precision and cost-effectiveness, the double-layer cylindrical and triple-layer dual-head J-PET geometry configurations seem promising for the future clinical application. Experimental tests are needed to confirm these findings., Comment: 19 pages, 7 pages

Grayscale lithography allows the creation of micrometer-scale features with spatially-controlled height in a process that is fully compatible with standard lithography. Here, solid immersion lenses are demonstrated in silicon carbide using a novel fabrication protocol combining grayscale lithography and hard-mask techniques to allow nearly hemispherical lenses of 5 $\mu$m radius to be etched into the substrate. The technique is highly scalable and compatible with CMOS technology, and device aspect ratios can be tuned after resist patterning by controlling the chemistry of the subsequent dry etch. These results provide a low-cost, high-throughput and industrially-relevant alternative to focused ion beam milling for the creation of high-aspect-ratio, rounded microstructures., Comment: 9 pages, 4 + 2 supplementary figures

Purpose In PBS particle therapy, short treatment delivery time is paramount for the efficient treatment of moving targets with motion mitigation techniques (such as breath-hold, rescanning, and gating). Energy and spot position change time are limiting factors in reducing treatment time. In this study, we designed a universal and dynamic energy modulator (ridge filter, RF) to broaden the Bragg peak, to reduce the number of energies and spots required to cover the target volume, thus lowering the treatment time. Methods Our RF unit comprises two identical RFs placed just before the isocenter. Both RFs move relative to each other, changing the Bragg peaks characteristics dynamically. We simulated different Bragg peak shapes with the RF in TOPAS and validated them experimentally. We then delivered single-field plans with 1Gy/fraction to different geometrical targets in water, to measure the dose delivery time using the RF and compare it with the clinical settings. Results Aligning the RFs in different positions produces different broadening in the Bragg peak; we achieved a maximum broadening of 2 cm. With RF we reduced the number of energies in a field by more than 60%, and the dose delivery time by 50%, for all geometrical targets investigated, without compromising the dose distribution transverse and distal fall-off. Conclusions Our novel universal and dynamic RF allows for the adaptation of the Bragg peak broadening for a spot and/or energy layer based on the requirement of dose shaping in the target volume. It significantly reduces the number of energy layers and spots to cover the target volume, and thus the treatment time. This RF design is ideal for ultra-fast treatment delivery within a single breath-hold (5-10 sec), efficient delivery of motion mitigation techniques, and small animal irradiation with ultra-high dose rates (FLASH)., Comment: 18 pages, 9 figures

The winds of massive stars are important for their direct impact on the interstellar medium, and for their influence on the final state of a star prior to it exploding as a supernova. However, the dynamics of these winds is understood primarily via their illumination from a single central source. The Doppler shift seen in resonance lines is a useful tool for inferring these dynamics, but the mapping from that Doppler shift to the radial distance from the source is ambiguous. Binary systems can reduce this ambiguity by providing a second light source at a known radius in the wind, seen from orbitally modulated directions. From the nature of the collision between the winds, a massive companion also provides unique additional information about wind momentum fluxes. Since massive stars are strong ultraviolet (UV) sources, and UV resonance line opacity in the wind is strong, UV instruments with a high resolution spectroscopic capability are essential for extracting this dynamical information. Polarimetric capability also helps to further resolve ambiguities in aspects of the wind geometry that are not axisymmetric about the line of sight, because of its unique access to scattering direction information. We review how the proposed MIDEX-scale mission Polstar can use UV spectropolarimetric observations to critically constrain the physics of colliding winds, and hence radiatively-driven winds in general. We propose a sample of 20 binary targets, capitalizing on this unique combination of illumination by companion starlight, and collision with a companion wind, to probe wind attributes over a range in wind strengths. Of particular interest is the hypothesis that the radial distribution of the wind acceleration is altered significantly, when the radiative transfer within the winds becomes optically thick to resonance scattering in multiple overlapping UV lines., Comment: 26 pages, 12 figures, Review in a topical collection series of Astrophysics and Space Sciences on the proposed Polstar satellite. arXiv admin note: substantial text overlap with arXiv:2111.11552

This resource focuses on recent changes in the data sources and measurements of Part B Indicators 1 and 2. It offers a side-by-side comparison of the State Performance Plan/Annual Performance Report (SPP/APR) Part B Indicator measurement tables for FFY 2019 and FFY 2020-2025 to highlight relevant differences in SPP/APR reporting of graduation rate and dropout rate. The resource specifically addresses the treatment of "alternate diploma" in the new calculation. For FFY 2019, the calculation of graduation rate included students receiving an alternate diploma in the numerator. For FFY 2020-2025, the calculation of graduation rate includes students receiving an alternate diploma in the denominator. The calculation for Indicator 2 remains similar from FFY 2019 to FFY 2020-2025; however, it explicitly adds students receiving an alternate diploma in the denominator.

This resource describes new reporting requirements and measurement changes to Part B State Performance Plan and Annual Performance Report (SPP/APR) Indicator 3. The majority of students with disabilities participate in regular statewide assessments, and a small percentage of students with the most significant disabilities participate in alternate assessments. In FFY 2020, OSEP requires states to disaggregate statewide assessment results for these two groups of students with disabilities (i.e., those who participate in the regular assessment and those who participate in the alternate assessment). OSEP also requires states to calculate a "proficiency rate gap" between students with and without disabilities who participate in the regular statewide assessment. The resource offers a side-by-side comparison of the SPP/APR Part B indicator measurement tables for FFY 2019 and FFY 2020 to highlight relevant differences in SPP/APR reporting of Indicator 3.

Massive star binaries are critical laboratories for measuring masses and stellar wind mass-loss rates. A major challenge is inferring viewing inclination and extracting information about the colliding wind interaction (CWI) region. Polarimetric variability from electron scattering in the highly ionized winds provides important diagnostic information about system geometry. We combine for the first time the well-known generalized treatment of \citet{brown_polarisation_1978} for variable polarization from binaries with the semi-analytic solution for the geometry and surface density CWI shock interface between the winds based on Canto et al 1996. Our calculations include some simplifications in the form of inverse square-law wind densities and the assumption of axisymmetry, but in so doing arrive at several robust conclusions. One is that when the winds are nearly equal (e.g., O\,+\,O binaries), the polarization has a relatively mild decline with binary separation. Another is that despite Thomson scattering being a gray opacity, the continuum polarization can show chromatic effects at ultraviolet wavelengths but will be mostly constant at longer wavelengths. Finally, when one wind dominates the other, as for example in WR+OB binaries, the polarization is expected to be larger at wavelengths where the OB component is more luminous, and generally smaller at wavelengths where the WR component is more luminous. This behavior arises because from the perspective of the WR star, the distortion of the scattering envelope from spherical is a minor perturbation situated far from the WR star. By contrast, the polarization contribution from the OB star is dominated by the geometry of the CWI shock., Comment: accepted for publication in the Astrophysical Journal. arXiv admin note: text overlap with arXiv:2111.11552

The COVID-19 pandemic has forced school leaders to make difficult decisions about how to balance students' educational needs with the health, safety, and social-emotional well-being of students and teachers. The American Rescue Plan Act of 2021 (Rescue Plan) recently enacted by Congress offers unprecedented amounts of potentially transformative funding to elementary and secondary schools. The Rescue Plan has the potential to simultaneously spur post-pandemic learning recovery efforts and address long-standing socio-demographic gaps in academic achievement and opportunity. This brief is intended to help state and local education leaders consider how to approach this opportunity to meet a persistent problem: the need for more educators of color to serve students. To do this, the authors encourage local education agencies (LEAs) to act strategically by leveraging the findings and evidence-based practices (EBP) of two distinct research bases: (1) High-dosage tutoring, extended-day programs, and summer learning programs are effective options for learning recovery; and (2) Students benefit from exposure to a diverse, representative educator workforce.

The Individuals with Disabilities Education Act (IDEA; P.L. 108-446) is the primary source of federal funding to states for the identification and education of children with disabilities. The majority of IDEA appropriations are allocated to states by formula to carry out activities under Part B, which covers 14 disability categories. Each state is responsible for ensuring that children with disabilities are found and evaluated. States must submit a plan to the Secretary of Education (the Secretary) that provides assurances that the state has policies in place to meet certain conditions. This report seeks to document the variability in state definitions of eligibility criteria in IDEA disability categories. The Congressional Research Service (CRS) conducted a survey of state regulations and other state department of education documents to identify operational definitions of eligibility criteria for each of the IDEA disability categories. CRS identified 15 states that have operational definitions of eligibility criteria with similar levels of detail for most of the disability categories. For these 15 states, CRS compared and contrasted state operational definitions of eligibility criteria to evaluate the size and scope of the variability. The survey results are grouped into three broad categories for analysis: (1) low-incidence disabilities; (2) medium-incidence disabilities; and (3) high-incidence disabilities. The results indicate there is uneven variability in state operational definitions of eligibility criteria for disabilities in terms of specificity, severity, method of identification, and timeline for identification. Eligibility criteria for low-incidence disabilities tend to be less variable than eligibility criteria for high-incidence disabilities. The greater variability in eligibility criteria for high-incidence disabilities may be reflective of ongoing debate surrounding the identification of these disabilities, most notably in the "specific learning disabilities" category.

Modern livestock farming is increasingly data driven and frequently relies on efficient remote sensing to gather data over wide areas. High resolution satellite imagery is one such data source, which is becoming more accessible for farmers as coverage increases and cost falls. Such images can be used to detect and track animals, monitor pasture changes, and understand land use. Many of the data driven models being applied to these tasks require ground truthing at resolutions higher than satellites can provide. Simultaneously, there is a lack of available aerial imagery focused on farmland changes that occur over days or weeks, such as herd movement. With this goal in mind, we present a new multi-temporal dataset of high resolution UAV imagery which is artificially degraded to match satellite data quality. An empirical blurring metric is used to calibrate the degradation process against actual satellite imagery of the area. UAV surveys were flown repeatedly over several weeks, for specific farm locations. This 5cm/pixel data is sufficiently high resolution to accurately ground truth cattle locations, and other factors such as grass cover. From 33 wide area UAV surveys, 1869 patches were extracted and artificially degraded using an accurate satellite optical model to simulate satellite data. Geographic patches from multiple time periods are aligned and presented as sets, providing a multi-temporal dataset that can be used for detecting changes on farms. The geo-referenced images and 27,853 manually annotated cattle labels are made publicly available., Comment: 16 pages, 7 figures, 2 tables

Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing. However, for many applications, synthetic data has been shown to have limited utility when used to train predictive models. One promising potential application of these data is in the exploratory phase of the machine learning workflow, which involves understanding, engineering and selecting features. This phase often involves considerable time, and depends on the availability of data. There would be substantial value in synthetic data that permitted these steps to be carried out while, for example, data access was being negotiated, or with fewer information governance restrictions. This paper presents an empirical analysis of the agreement between the feature importance obtained from raw and from synthetic data, on a range of artificially generated and real-world datasets (where feature importance represents how useful each feature is when predicting a the outcome). We employ two differentially-private methods to produce synthetic data, and apply various utility measures to quantify the agreement in feature importance as this varies with the level of privacy. Our results indicate that synthetic data can sometimes preserve several representations of the ranking of feature importance in simple settings but their performance is not consistent and depends upon a number of factors. Particular caution should be exercised in more nuanced real-world settings, where synthetic data can lead to differences in ranked feature importance that could alter key modelling decisions. This work has important implications for developing synthetic versions of highly sensitive data sets in fields such as finance and healthcare., Comment: 27 pages, 8 figures

One objective of the Polstar spectropolarimetry mission is to characterize the degree of nonconservative mass transfer that occurs at various stages of binary evolution, from the initial mass reversal to the late Algol phase. The proposed instrument combines spectroscopic and polarimetric capabilities, where the spectroscopy can resolve Doppler shifts in UV resonance lines with 10 km/s precision, and polarimetry can resolve linear polarization with 1e-3 precision or better. The spectroscopy will identify absorption by mass streams seen in projection against the stellar disk as a function of orbital phase, hot accretion spots, as well as scattering from extended splash structures, circumbinary disks, and other flows in and above/below the orbital plane (e.g. jets) that fail to be transferred conservatively. The polarimetry affects more the light coming from material not seen against the stellar disk, allowing the geometry of the scattering to be tracked, resolving ambiguities left by the spectroscopy and light-curve information. For example, nonconservative mass streams ejected in the polar direction will produce polarization of the opposite sign from conservative transfer accreting in the orbital plane. Also, time domain coverage over a range of phases of the binary orbit are well supported by the Polstar observing strategy. Combining these elements will significantly improve our understanding of the mass transfer process and the amount of mass that can escape from the system, an important channel for changing the final mass, and ultimate supernova, of the large number of massive stars found in binaries at close enough separation to undergo interaction., Comment: Refereed paper in Ap&SS 367:Topical Collection, 23 pages, 10 figures

As sources of chemical enrichment, ionizing radiation and energetic feedback, massive stars drive the ecology of their host galaxies despite their relative rarity, additionally to yielding compact remnants, which can generate gravitational waves. The evolution of massive stars is crucially informed by their detailed mass-loss history; however, wind structures on a variety of scales cause important uncertainties on their mass-loss rates. Binary systems can place further constraints on the mass-loss properties of massive stars, especially colliding-wind binaries. In this paper, we review how the proposed MIDEX-scale mission Polstar can critically constrain the physics of colliding winds (and hence radiatively-driven winds in general) with ultraviolet spectropolarimetric observations, providing an unprecedented improvement on the accuracy of the determination of both mass-loss rates and the velocity structure of the winds of massive stars. We propose a sample of 17 targets that will allow us to study a variety of wind-colliding systems spanning a large parameter space using the spatial information yielded by both spectroscopic and polarimetric data obtained with Polstar., Comment: 21 pages, 12 figures 1 table, Whitepaper

Polstar is a proposed NASA MIDEX mission that would feature a high resolution UV spectropolarimeter capable of measure all four Stokes parameters onboard a 60cm telescope. The mission would pioneer the field of time-domain UV spectropolarimetry. Time domain UV spectropolarimetry offers the best resource to determine the geometry and physical conditions of protoplanetary disks from the stellar surface to <5 AU. We detail two key objectives that a dedicated time domain UV spectropolarimetry survey, such as that enabled by Polstar, could achieve: 1) Test the hypothesis that magneto-accretion operating in young planet-forming disks around lower-mass stars transitions to boundary layer accretion in planet-forming disks around higher mass stars; and 2) Discriminate whether transient events in the innermost regions of planet-forming disks of intermediate mass stars are caused by inner disk mis-alignments or from stellar or disk emissions., Comment: 16 pages, 7 figures

Knowing where livestock are located enables optimized management and mustering. However, Australian farms are large meaning that many of Australia's livestock are unmonitored which impacts farm profit, animal welfare and the environment. Effective animal localisation and counting by analysing satellite imagery overcomes this management hurdle however, high resolution satellite imagery is expensive. Thus, to minimise cost the lowest spatial resolution data that enables accurate livestock detection should be selected. In our work, we determine the association between object detector performance and spatial degradation for cattle, sheep and dogs. Accurate ground truth was established using high resolution drone images which were then downsampled to various ground sample distances (GSDs). Both circular and cassegrain aperture optics were simulated to generate point spread functions (PSFs) corresponding to various optical qualities. By simulating the PSF, rather than approximating it as a Gaussian, the images were accurately degraded to match the spatial resolution and blurring structure of satellite imagery. Two existing datasets were combined and used to train and test a YoloV5 object detection network. Detector performance was found to drop steeply around a GSD of 0.5m/px and was associated with PSF matrix structure within this GSD region. Detector mAP performance fell by 52 percent when a cassegrain, rather than circular, aperture was used at a 0.5m/px GSD. Overall blurring magnitude also had a small impact when matched to GSD, as did the internal network resolution. Our results here inform the selection of remote sensing data requirements for animal detection tasks, allowing farmers and ecologists to use more accessible medium resolution imagery with confidence., Comment: 20 pages, 9 figures, 4 tables in appendix

In a recent study (Jozinovi\'c et al, 2020) we showed that convolutional neural networks (CNNs) applied to network seismic traces can be used for rapid prediction of earthquake peak ground motion intensity measures (IMs) at distant stations using only recordings from stations near the epicenter. The predictions are made without any previous knowledge concerning the earthquake location and magnitude. This approach differs from the standard procedure adopted by earthquake early warning systems (EEWSs) that rely on location and magnitude information. In the previous study, we used 10 s, raw, multistation waveforms for the 2016 earthquake sequence in central Italy for 915 events (CI dataset). The CI dataset has a large number of spatially concentrated earthquakes and a dense station network. In this work, we applied the CNN model to an area around the VIRGO gravitational waves observatory sited near Pisa, Italy. In our initial application of the technique, we used a dataset consisting of 266 earthquakes recorded by 39 stations. We found that the CNN model trained using this smaller dataset performed worse compared to the results presented in the original study by Jozinovi\'c et al. (2020). To counter the lack of data, we adopted transfer learning (TL) using two approaches: first, by using a pre-trained model built on the CI dataset and, next, by using a pre-trained model built on a different (seismological) problem that has a larger dataset available for training. We show that the use of TL improves the results in terms of outliers, bias, and variability of the residuals between predicted and true IMs values. We also demonstrate that adding knowledge of station positions as an additional layer in the neural network improves the results. The possible use for EEW is demonstrated by the times for the warnings that would be received at the station PII.

Obtaining up to date information on the number of UK COVID-19 regional infections is hampered by the reporting lag in positive test results for people with COVID-19 symptoms. In the UK, for "Pillar 2" swab tests for those showing symptoms, it can take up to five days for results to be collated. We make use of the stability of the under reporting process over time to motivate a statistical temporal model that infers the final total count given the partial count information as it arrives. We adopt a Bayesian approach that provides for subjective priors on parameters and a hierarchical structure for an underlying latent intensity process for the infection counts. This results in a smoothed time-series representation now-casting the expected number of daily counts of positive tests with uncertainty bands that can be used to aid decision making. Inference is performed using sequential Monte Carlo.

Purpose: The purpose of this work was to provide a flexible platform for FLASH research with protons by adapting a former clinical pencil beam scanning gantry to irradiations with ultrahigh dose rates. Methods: PSI Gantry 1 treated patients until December 2018. We optimized the beamline parameters to transport the 250 MeV beam extracted from the PSI COMET accelerator to the treatment room, maximizing the transmission of beam intensity to the sample. We characterized a dose monitor on the gantry to ensure good control of the dose, delivered in spot-scanning mode. We characterized the beam for different dose rates and field sizes for transmission irradiations. We explored scanning possibilities in order to enable conformal irradiations or transmission irradiations of large targets (with transverse scanning). Results: We achieved a transmission of 86 % from the cyclotron to the treatment room. We reached a peak dose rate of 9000 Gy/s at 3 mm water equivalent depth, along the central axis of a single pencil beam. Field sizes of up to 5x5 mm$^{2}$ were achieved for single spot FLASH irradiations. Fast transverse scanning allowed to cover a field of 16x1.2 cm$^{2}$. With the use of a nozzle-mounted range shifter we are able to span depths in water ranging from 19.6 to 37.9 cm. Various dose levels were delivered with a precision within less than 1 %. Conclusions: We have realized a proton FLASH irradiation setup able to investigate continuously a wide dose rate spectrum, from 1 to 9000 Gy/s in a single spot irradiation as well as in the pencil beam scanning mode. As such, we have developed a versatile test bench for FLASH research., Comment: Submitted to Medical Physics

The global food system faces various endogeneous and exogeneous, biotic and abiotic risk factors, including a rising human population, higher population densities, price volatility and climate change. Quantitative models play an important role in understanding food systems' expected responses to shocks and stresses. Here, we present a stylised mathematical model of a national-level food system that incorporates domestic supply of a food commodity, international trade, consumer demand, and food commodity price. We derive a critical compound parameter signalling when domestic supply will become unsustainable and the food system entirely dependent on imports, which results in higher commodity prices, lower consumer demand and lower inventory levels. Using Bayesian estimation, we apply the dynamic food systems model to infer the sustainability of the UK pork industry. We find that the UK pork industry is currently sustainable but because the industry is dependent on imports to meet demand, a decrease in self-sufficiency below 50% (current levels are 60-65%) would lead it close to the critical boundary signalling its collapse. Our model provides a theoretical foundation for future work to determine more complex causal drivers of food system vulnerability.

We report on over 13 years of optical and near-ultraviolet spectropolarimetric observations of the famous Luminous Blue Variable (LBV), P Cygni. LBVs are a critical transitional phase in the lives of the most massive stars, and achieve the largest mass-loss rates of any group of stars. Using spectropolarimetry, we are able to learn about the geometry of the near circumstellar environment surrounding P Cygni and gain insights into LBV mass-loss. Using data from the HPOL and WUPPE spectropolarimeters, we estimate the interstellar polarization contribution to P Cygni's spectropolarimetric signal, analyze the variability of the polarization across the H$\alpha$ emission line, search for periodic signals in the data, and introduce a statistical method to search for preferred position angles in deviations from spherical symmetry which is novel to astronomy. Our data are consistent with previous findings, showing free-electron scattering off of clumps uniformly distributed around the star. This is complicated, however, by structure in the percent-polarization of the H$\alpha$ line and a series of previously undetected periodicities.

The Covid-19 pandemic has resulted in a variety of approaches for managing infection outbreaks in international populations. One example is mobile phone applications, which attempt to alert infected individuals and their contacts by automatically inferring two key components of infection risk: the proximity to an individual who may be infected, and the duration of proximity. The former component, proximity, relies on Bluetooth Low Energy (BLE) Received Signal Strength Indicator(RSSI) as a distance sensor, and this has been shown to be problematic; not least because of unpredictable variations caused by different device types, device location on-body, device orientation, the local environment and the general noise associated with radio frequency propagation. In this paper, we present an approach that infers posterior probabilities over distance given sequences of RSSI values. Using a single-dimensional Unscented Kalman Smoother (UKS) for non-linear state space modelling, we outline several Gaussian process observation transforms, including: a generative model that directly captures sources of variation; and a discriminative model that learns a suitable observation function from training data using both distance and infection risk as optimisation objective functions. Our results show that good risk prediction can be achieved in $\mathcal{O}(n)$ time on real-world data sets, with the UKS outperforming more traditional classification methods learned from the same training data.

Particle therapy is a growing cancer treatment modality worldwide. However, there still remains a number of unanswered questions considering differences in the biological response between particles and photons. These questions, and probing of biological mechanisms in general, necessitate experimental investigation. The Infrastructure in Proton International Research (INSPIRE) project was created to provide an infrastructure for European research, unify research efforts on the topic of proton and ion therapy across Europe, and to facilitate the sharing of information and resources. This work highlights the radiobiological capabilities of the INSPIRE partners, providing details of physics (available particle types and energies), biology (sample preparation and post-irradiation analysis), and researcher access (the process of applying for beam time). The collection of information reported here is designed to provide researchers both in Europe and worldwide with the tools required to select the optimal center for their research needs. We also highlight areas of redundancy in capabilities and suggest areas for future investment., Comment: 18 pages