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A three-day seminar for nurses was conducted to improve their ability to communicate effectively with other people. The method used in this seminar was microteaching. The basic ingredients of the microteaching concept are the communication techniques dimension, the teach-reteach dimension, and the immediate feedback dimension. Under the direction of a supervisor and working with others in the seminar, each participant demonstrated and spoke on the topic of her choice, with the aim of instructing the listeners. Each demonstration was recorded on video tape. The tape was viewed and analysed, followed by direct question and answer sessions and suggestions for improvement by the supervisor. The benefit of immediate feedback and reaction was apparent, and each participant developed more self-confidence as the seminar progressed. The concensus of opinion at the end of the session was that microteaching is a valuable tool not only for improving communication skills but also for improving teaching techniques. (JD)

Logical predictions about relationships between school aptitude and standardized achievement, aptitude and teachers' grades, and teachers' grades and standardized achievement can be made from the literature. These predictions are that (1) conventional school aptitude measures should predict standardized achievement test scores equally well for boys and girls but better for advantaged than disadvantaged children; (2) teachers' marks are more accurate for girls than for boys when judged against the sexes' standardized achievement test scores; are more accurate for middle-class than for disadvantaged children; and are least accurate for disadvantaged black males; and (3) teachers consistently give girls higher grades than boys but there are no important differences between boys' and girls' achievement when measured by standard achievement tests. The present study was conducted to test the strength of the relationships between pupil aptitude, standardized achievement and teachers' grades and to determine the percent of variance in grade point average accounted for by aptitude and standardized achievement in a representative sample of fifth- and ninth-grade Mexican-American, Black and Anglo students. (Author/RC)

The completed WISC-R's (Wechsler Intelligence Scale for Children-Revised) of 76 white urban children with academic problems (6 years, 0 months to 15 years, 9 months) were rescored utilizing the Satz and Mogel criteria for an abbreviated intelligence measure. Extremely high correlations for IQ's (.96 - .98) and subtests (.66 - .95) were found. However, when mean differences between complete WISC-R and the shortened form were examined, significant differences between administrations were found. Furthermore, one third of the subjects showed changes in intelligence classification levels when the abbreviated form was used. Thus, two of the three criteria previously suggested for a valid abbreviated intelligence test of: (1) high correlation between administration forms; (2) non significant t-tests between the abbreviated and standard form mean IQ; and (3) low percentage of IQ classification change with the administration of the short form were not met. It was concluded, however, that the abbreviated WISC-R may be appropriate when intelligence is a question relative to candidacy for therapy or as a non-critical, general indication of intelligence when IQ classification is not important and/or assessment time is limited. (Author/RC)

Preceding the body of the report, a brief review of the literature is provided to acquaint the reader with similarities and differences between national and local trends regarding the demographic characteristics of the physician population. The goal of the statewide residency study was to develop a strategy for the design and allocation of physician residencies consistent with statewide needs. A graphic model of the physician manpower production process was developed which enhanced understanding of the manpower problems facing Louisiana. Through the model, available data, and personal interviews with senior medical students and postgraduate trainees, data were compiled and analyzed regarding the need for physicians in Louisiana in 1982, where and how the number of physicians can be increased, the status of primary care treatment, likely sites for practicing physicians, and related concerns. The general conclusions point to several significant manpower production problems in Louisiana in its preparation for future needs for physician services. The study committee proposed several recommendations to meet the problem. (Appendixes contain supplementary tables and interview forms.) (AG)

The goal of Smithsonian Science for North and South Carolina Classrooms was to provide teachers with ongoing, differentiated professional development and research-based curricular materials to improve elementary student achievement in science, mathematics, and reading. This work used an inquiry-based science curriculum, Smithsonian Science for the Classroom, which is aligned with the Next Generation Science Standards (NGSS), and was implemented in Grades 3-5 within predominantly rural North and South Carolina school districts serving high-needs students. The Center for Research in Educational Policy (CREP) at the University of Memphis, a State of Tennessee Center of Excellence, was the independent third-party evaluator. CREP implemented a Randomized Controlled Trial (RCT) to collect and analyze data using a rigorous, mixed-methods approach, including quantitative analyses of student achievement data from the Stanford-10 and state assessments, and qualitative analyses of classroom observation data, as well as teacher feedback from professional development surveys, module logs, and focus groups. For this study, 36 schools (including one split cohort being treated as one school) in seven districts within North and South Carolina were randomly assigned to treatment and comparison groups. The study cohort, followed over three academic years (2020-21 through 2022-23), was composed of more than 1,600 third grade (2020-21) students in these schools. In the comparison condition, schools used their business-as-usual science curricula and teacher professional development and did not receive Smithsonian Science curricular materials or professional development. As the pretests for achievement outcomes, students took the Abbreviated Battery of the Stanford Achievement Test Series, Tenth Edition (Stanford-10) in Reading and Math in spring of 2021 (the cohort's third grade year). The main findings and posttests included the combined sample (i.e., both states combined) for (a) the Stanford-10 Science subtest, which was administered in the spring of 2023 (the cohort's fifth grade year), and (b) spring 2023 standardized state assessment scores in Reading and Math. Using a hierarchical linear model (HLM) with school as a random effect, the analysis of the effect of Smithsonian Science for the three main findings after several years of disruptions from the COVID-19 pandemic was (a) positive (g = 0.18) and statistically significant (p = 0.032) on the Stanford-10 science assessment and (b) positive for both Reading (g = 0.10) and Math (g = 0.16), meaning students in the treatment group performed better than the control group, but the effects were not statistically significant. Teachers were generally positive in terms of the professional development provided, and feedback on the module logs largely supported the effectiveness of the professional development and fidelity of implementation. Classroom observations further supported the effectiveness of the professional development and fidelity to inquiry-based practices in treatment classrooms (e.g., use of experiential hands-on learning and level of class time dedicated to inquiry-based science). With instructional time for science lagging other subject areas, and as learning recovery in reading and math after COVID-19 receive national attention, the results demonstrate that ongoing, differentiated, high-quality professional learning and high-quality instructional materials for science instruction can support student achievement in science, math, and reading.

This report arrives during a time of heightened scrutiny and civic engagement. While public attention is currently trained primarily on Milwaukee Public Schools (MPS), this research encompasses the whole of the city's education system, marking both commonalities and differences between different types of publicly funded schools. It highlights financial aspects of the system but also expands the discussion to include student enrollment and outcomes. The report is organized into three major sections: Milwaukee's Students and Schools, covering the basic schooling options available to students along with student enrollment and demographic trends; School Funding in Milwaukee, outlining the core funding mechanisms and their funding levels for schools in the city; and Student Outcomes and School Performance, summarizing broad trends in Milwaukee's academic results. The report concludes with key insights for the consideration of both policymakers and the public. It is hoped the report's findings ground both current and future policy discussions with important facts and nonpartisan insights. The authors further intend to inform those discussions with a second report this fall, which will highlight promising K-12 practices and innovations occurring both within Milwaukee and nationally.

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai., Comment: 25 pages, 6 figures

As AI systems become more capable, widely deployed, and increasingly autonomous in critical areas such as cybersecurity, biological research, and healthcare, ensuring their safety and alignment with human values is paramount. Machine unlearning -- the ability to selectively forget or suppress specific types of knowledge -- has shown promise for privacy and data removal tasks, which has been the primary focus of existing research. More recently, its potential application to AI safety has gained attention. In this paper, we identify key limitations that prevent unlearning from serving as a comprehensive solution for AI safety, particularly in managing dual-use knowledge in sensitive domains like cybersecurity and chemical, biological, radiological, and nuclear (CBRN) safety. In these contexts, information can be both beneficial and harmful, and models may combine seemingly harmless information for harmful purposes -- unlearning this information could strongly affect beneficial uses. We provide an overview of inherent constraints and open problems, including the broader side effects of unlearning dangerous knowledge, as well as previously unexplored tensions between unlearning and existing safety mechanisms. Finally, we investigate challenges related to evaluation, robustness, and the preservation of safety features during unlearning. By mapping these limitations and open challenges, we aim to guide future research toward realistic applications of unlearning within a broader AI safety framework, acknowledging its limitations and highlighting areas where alternative approaches may be required.

Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing technologies. The proposal to use nuclear and electronic spins of donor atoms in silicon, introduced by Kane in 1998, sparked a new research field focused on the precise positioning of individual impurity atoms for quantum devices, utilising scanning tunnelling microscopy and ion implantation. This roadmap article reviews the advancements in the 25 years since Kane's proposal, the current challenges, and the future directions in atomic-scale semiconductor device fabrication and measurement. It covers the quest to create a silicon-based quantum computer and expands to include diverse material systems and fabrication techniques, highlighting the potential for a broad range of semiconductor quantum technological applications. Key developments include phosphorus in silicon devices such as single-atom transistors, arrayed few-donor devices, one- and two-qubit gates, three-dimensional architectures, and the development of a toolbox for future quantum integrated circuits. The roadmap also explores new impurity species like arsenic and antimony for enhanced scalability and higher-dimensional spin systems, new chemistry for dopant precursors and lithographic resists, and the potential for germanium-based devices. Emerging methods, such as photon-based lithography and electron beam manipulation, are discussed for their disruptive potential. This roadmap charts the path toward scalable quantum computing and advanced semiconductor quantum technologies, emphasising the critical intersections of experiment, technological development, and theory., Comment: 94 pages

Fundamental weak interactions have been shown to violate parity in both nuclear and atomic systems. However, observation of parity violation in a molecular system has proven an elusive target. Nuclear spin dependent contributions of the weak interaction are expected to result in energetic differences between enantiomers manifesting in nuclear magnetic resonance (NMR) spectra as chemical shift differences on the order of $10^{-6}$ Hz to $10^{-3}$ Hz for high-$Z$ nuclei. By employing simultaneous measurements of the diastereomeric splittings for a light and a heavy nucleus in solution-state NMR, residual chemical shift differences persisting in non-chiral environment between enantiomers of chiral compounds smaller than the typical linewidth of high-field NMR may be resolved. Sources of error must be identified and minimized to verify that the observed effect is, in fact, due to parity violation and not systematic effects. This paper presents a detailed analysis of a system incorporating \textsuperscript{31}P and \textsuperscript{1}H NMR to elucidate the systematic effects and to guide experiments with higher-$Z$ nuclei where molecular parity violation may be resolved.

In the relentless pursuit of advancing semiconductor technologies, the demand for atomic layer processes has given rise to innovative processes, which have already played a significant role in the continued miniaturization features. Among these, atomic layer etching (ALE) is gaining increasing attention, offering precise control over material removal at the atomic level. Despite some thermal ALE achieved sub-nm etching controllability, the currently practical ALE processes that involve plasmas steps often suffer from high etch rates due to the scarcity of highly synergistic ALE half-reactions. To overcome this limitation, we developed an ALE process of silicon dioxide (SiO$_2$) on a silicon wafer using sequential pure sulfur hexafluoride (SF6$_6$ gas exposure and argon (Ar) plasma etching near room temperature, achieving a stable and consistent etching rate of approximately 1.4 {\AA}/cycle. In this process, neither of the two half-cycle reactions alone produces etching effects, and etching only occurs when the two are repeated in sequence, which means a 100% synergy. The identification of temperature and plasma power windows further substantiates the high synergy of our ALE process. Moreover, detailed morphology characterization over multiple cycles reveals a directional etching effect. This study provides a reliable, reproducible, and highly controllable ALE process for SiO$_2$ etching, which is promising for nanofabrication processes.

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

Gaussian processes (GPs) and Gaussian random fields (GRFs) are essential for modelling spatially varying stochastic phenomena. Yet, the efficient generation of corresponding realisations on high-resolution grids remains challenging, particularly when a large number of realisations are required. This paper presents two novel contributions. First, we propose a new methodology based on Dirichlet-Neumann averaging (DNA) to generate GPs and GRFs with isotropic covariance on regularly spaced grids. The combination of discrete cosine and sine transforms in the DNA sampling approach allows for rapid evaluations without the need for modification or padding of the desired covariance function. While this introduces an error in the covariance, our numerical experiments show that this error is negligible for most relevant applications, representing a trade-off between efficiency and precision. We provide explicit error estimates for Mat\'ern covariances. The second contribution links our new methodology to the stochastic partial differential equation (SPDE) approach for sampling GRFs. We demonstrate that the concepts developed in our methodology can also guide the selection of boundary conditions in the SPDE framework. We prove that averaging specific GRFs sampled via the SPDE approach yields genuinely isotropic realisations without domain extension, with the error bounds established in the first part remaining valid., Comment: 30 pages, 7 figures, pre-print

Precision radial velocity (RV) spectrographs that use adaptive optics (AO) show promise to advance telescope observing capabilities beyond those of seeing-limited designs. We are building a spectrograph for the Large Binocular Telescope (LBT) named iLocater that uses AO to inject starlight directly into single mode fibers (SMF). iLocater's first acquisition camera system (the `SX' camera), which receives light from one of the 8.4m diameter primary mirrors of the LBT, was initially installed in summer 2019 and has since been used for several commissioning runs. We present results from first-light observations that include on-sky measurements as part of commissioning activities. Imaging measurements of the bright B3IV star 2 Cygni ($V=4.98$) resulted in the direct detection of a candidate companion star at an angular separation of only $\theta = 70$ mas. Follow-up AO measurements using Keck/NIRC2 recover the candidate companion in multiple filters. An $R\approx1500$ miniature spectrograph recently installed at the LBT named ``Lili'' provides spatially resolved spectra of each binary component, indicating similar spectral types and strengthening the case for companionship. Studying the multiplicity of young runaway star systems like 2 Cygni ($36.6 \pm 0.5$ Myr) can help to understand formation mechanisms for stars that exhibit anomalous velocities through the galaxy. This on-sky demonstration illustrates the spatial resolution of the iLocater SX acquisition camera working in tandem with the LBT AO system; it further derisks a number of technical hurdles involved in combining AO with Doppler spectroscopy., Comment: Accepted to AJ

The variations of oxygen abundance and ionization parameter in HII regions are usually thought to be the dominant factors that produced variations seen in observed emission line spectra. However, if and how these two quantities are physically related is hotly debated in the literature. Using emission line data of NGC 628 observed with SITELLE as part of the Star-formation, Ionized Gas, and Nebular Abundances Legacy Survey (SIGNALS), we use a suite of photoionization models to constrain the abundance and ionization parameters for over 1500 HII regions throughout its disk. We measure an anti-correlation between these two properties, consistent with expectations, although with considerable scatter. Secondary trends with dust extinction and star formation rate surface density potentially explain the large scatter observed. We raise concerns throughout regarding various modeling assumptions and their impact on the observed correlations presented in the literature., Comment: 27 pages, 12 figures, 2 tables. Accepted to ApJ

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, distributed quantum-assisted probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability., Comment: 50 pages, 42 figures

Boundary conforming coordinates are commonly used in plasma physics to describe the geometry of toroidal domains, for example, in three-dimensional magnetohydrodynamic equilibrium solvers. The magnetohydrodynamic equilibrium configuration can be approximated with an inverse map, defining nested surfaces of constant magnetic flux. For equilibrium solvers that solve for this inverse map iteratively, the initial guess for the inverse map must be well defined and invertible. Even if magnetic islands are to be included in the representation, boundary conforming coordinates can still be useful, for example to parametrize the interface surfaces in multi-region, relaxed magnetohydrodynamics. Given a fixed boundary shape, finding a valid boundary conforming mapping can be challenging, especially for the non-convex boundaries from recent developments in stellarator optimization. In this work, we propose a new algorithm to construct such a mapping, by solving two Dirichlet-Laplace problems via a boundary integral method. We can prove that the generated harmonic map is always smooth and has a smooth inverse. Furthermore, we can find a discrete approximation of the mapping that preserves this property.

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

The author's statement to the U.S. Senate Committee on Health, Education, Labor & Pensions on the challenges faced by America's classroom teachers focuses on a few of the factors that lead to teacher frustration and burnout that higher pay, however well-intended, does not change. They include, but are not limited to, poor teacher preparation, deteriorating classroom conditions--specifically classroom disorder and disruption--shoddy curriculum, and increasingly the expectation that they will not just teach reading, math, or their subject areas effectively, but also play a quasi-therapeutic role in response to students' behavioral and mental health needs. We are asking teachers to do too many things to do any of them well at any salary.

This report describes results from the Long-Term Impact of Early College High Schools Study--funded by the Institute of Education Sciences (IES) (#R305A210017)--which aimed to explore the long-term impacts of early college (EC) high schools on students' academic outcomes (e.g., college enrollment, degree attainment) and workforce, financial, and later life outcomes after schooling. In this report--the second follow-up report on our initial EC impact study--we focus specifically on key questions about workforce, financial, and other life outcomes: What were the impacts of ECs on workforce, financial, and other life outcomes in the 12th to 14th years after expected high school graduation? Did the impacts of ECs vary by participant characteristics? This report describes findings which build on a previous EC impact study, which was a multisite student-level randomized controlled trial with randomization based on admission lotteries. The analyses in this report focus on individuals who originally participated in 17 admission lotteries conducted by seven ECs for three cohorts of students, and examined outcomes after formal schooling. Key takeaways include the following: (1) Participants who were admitted to an EC, regardless of whether they attended the EC, did not experience a significant effect on any of the workforce, financial, and other life outcomes measured with survey data 12 to 14 years after expected high school graduation; and (2) EC impacts on workforce, financial, and other life outcomes measured 12 to 14 years after expected high school graduation did not differ significantly by individuals' race/ethnicity, low-income status, or prior achievement. While our initial impact study and first follow-up study found that attending an EC had effects on secondary and postsecondary enrollment, and completion for participants with different background characteristics, we found that attending an EC had no impact on any of the workforce, financial, and other life outcomes that we analyzed 12 to 14 years after participants' expected high school graduation. Future studies could consider examining workforce, financial, and other life outcomes in years before the 12th to 14th year after expected high school graduation using administrative data sources (e.g., IRS or unemployment insurance records). Further research may also examine if other factors, such as EC students' college major or labor market opportunities, influence the impact of ECs on longer-term outcomes.

The EdResearch for Action "Overview Series" summarizes the research on key topics to provide K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students. This overview brief discusses the central question: What is the evidence on strategies to build a sense of school connectedness and engagement among all students? Key insights are arranged in the following sections: (1) breaking down the issue; (2) evidence-based practices; and (3) practices to avoid. [The BARR Center and Network for College Success are additional collaborators for this report.]

Chronic rhinosinusitis (CRS) is a common and persistent sinus imflammation that affects 5 - 12\% of the general population. It significantly impacts quality of life and is often difficult to assess due to its subjective nature in clinical evaluation. We introduce PARASIDE, an automatic tool for segmenting air and soft tissue volumes of the structures of the sinus maxillaris, frontalis, sphenodalis and ethmoidalis in T1 MRI. By utilizing that segmentation, we can quantify feature relations that have been observed only manually and subjectively before. We performed an exemplary study and showed both volume and intensity relations between structures and radiology reports. While the soft tissue segmentation is good, the automated annotations of the air volumes are excellent. The average intensity over air structures are consistently below those of the soft tissues, close to perfect separability. Healthy subjects exhibit lower soft tissue volumes and lower intensities. Our developed system is the first automated whole nasal segmentation of 16 structures, and capable of calculating medical relevant features such as the Lund-Mackay score.

Poisson autoregressive count models have evolved into a time series staple for correlated count data. This paper proposes an alternative to Poisson autoregressions: count echo state networks. Echo state networks can be statistically analyzed in frequentist manners via optimizing penalized likelihoods, or in Bayesian manners via MCMC sampling. This paper develops Poisson echo state techniques for count data and applies them to a massive count data set containing the number of graduate students from 1,758 United States universities during the years 1972-2021 inclusive. Negative binomial models are also implemented to better handle overdispersion in the counts. Performance of the proposed models are compared via their forecasting performance as judged by several methods. In the end, a hierarchical negative binomial based echo state network is judged as the superior model.

We present a compact scintillating fibre timing detector developed for the Mu3e experiment. Mu3e is one of the flagship experiments of the Swiss particle physics scene, aiming to search for the charged lepton flavour violating (neutrinoless) muon decay $\mu^+ \rightarrow e^+e^-e^+$. Mu3e is planned to start taking data in 2025 at the Paul Scherrer Institute in Switzerland, using the most intense continuous surface muon beam in the world (10$^8$ muons per second). At the University of Geneva, together with partners from ETH Zurich, we are developing a scintillating fibre detector formed by staggering three layers of 250 $\mu m$ diameter round scintillating fibres. The fibre ribbons are coupled at both ends to multi-channel silicon photo-multiplier arrays, which are read out with the MuTRiG ASIC, specifically developed for this experiment. This presentation is focused on the performances of the scintillating fibre detector, notably on the time resolution around 250 ps, the efficiency greater than 97\% and the spatial resolution of $\sim$ 100 $\mu m$. In this presentation, we also include the challenges overcome to build this very thin scintillating fibre detector, having a thickness smaller than 0.2\% of the radiation length. Furthermore, we discuss the operation and performance of the MuTRiG ASIC, used for reading out the 3072 channels of the fibre detector.

Mu3e is an experiment currently under construction at the Paul Scherrer Institute in Switzerland, designed to search for the Lepton Flavor Violating (LFV) decay $\mu^+ \rightarrow e^+e^-e^+$. In extensions of the Standard Model (SM) that account for neutrino masses, this decay is theoretically allowed but occurs only through extremely rare loop processes, with a predicted branching ratio of approximately $\mathcal{O}(10^{-54})$. Such a small probability implies that any observation of this decay would provide clear evidence for physics beyond the SM. The Mu3e experiment aims to probe the $\mu^+ \rightarrow e^+e^-e^+$ decay with a sensitivity of approximately $\mathcal{O}(10^{-15})$ in its Phase-1 and plans to achieve a sensitivity of $\mathcal{O}(10^{-16})$ after future upgrades. To reach its Phase-1 ambitious goals, Mu3e is going to use the most intense continuous muon beam in the world, generating 10$^{8}$ muon stops per second in the target placed at the center of the Mu3e. Mu3e will use three main technologies for particle detection. The tracking will done through ultra-thin (50 - 70 $\mu m$) pixel detectors based on MuPix11 sensors. These are high-voltage monolithic active pixel sensors (HV-MAPS) with a $\sim$ 23~$\mu$m spatial resolution. The timing will be done through scintillating fibres ($\sim$ 250 ps) and tiles ($\sim$ 40 ps), coupled to silicon photomultipliers and read out by MuTRiG3 ASICs. A triggerless DAQ system based on FPGAs will collect data from the detectors, which will then undergo reconstruction in a GPU filter farm. The assembly of the detectors has started, with a detector commissioning beam time planned for 2025. This document reports on the status of the construction, installation, and data-taking plans for the near future.

Dynamic High-Level Synthesis (HLS) uses additional hardware to perform memory disambiguation at runtime, increasing loop throughput in irregular codes compared to static HLS. However, most irregular codes consist of multiple sibling loops, which currently have to be executed sequentially by all HLS tools. Static HLS performs loop fusion only on regular codes, while dynamic HLS relies on loops with dependencies to run to completion before the next loop starts. We present dynamic loop fusion for HLS, a compiler/hardware co-design approach that enables multiple loops to run in parallel, even if they contain unpredictable memory dependencies. Our only requirement is that memory addresses are monotonically non-decreasing in inner loops. We present a novel program-order schedule for HLS, inspired by polyhedral compilers, that together with our address monotonicity analysis enables dynamic memory disambiguation that does not require searching of address histories and sequential loop execution. Our evaluation shows an average speedup of 14$\times$ over static and 4$\times$ over dynamic HLS., Comment: To appear in the Proceedings of the 2025 ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA 2025)

Many classical and modern finite element spaces are derived by dividing each computational cell into finer pieces. Such \emph{macroelements} frequently enable the enforcement of mathematically desirable properties such as divergence-free conditions or $C^1$ continuity in a simpler or more efficient manner than elements without the subdivision. Although a few modern software projects provide one-off support for particular macroelements, a general approach facilitating broad-based support has, until now, been lacking. In this work, we describe a major addition to the FIAT project to support a wide range of different macroelements. These enhancements have been integrated into the Firedrake code stack. Numerical evaluation of the new macroelement facility is provided.

The deployment of PV inverters is rapidly expanding across Europe, where these devices must increasingly comply with stringent grid requirements.This study presents a benchmark analysis of four PV inverter manufacturers, focusing on their Fault Ride Through capabilities under varying grid strengths, voltage dips, and fault durations, parameters critical for grid operators during fault conditions.The findings highlight the influence of different inverter controls on key metrics such as total harmonic distortion of current and voltage signals, as well as system stability following grid faults.Additionally, the study evaluates transient stability using two distinct testing approaches.The first approach employs the current standard method, which is testing with an ideal voltage source. The second utilizes a Power Hardware in the Loop methodology with a benchmark CIGRE grid model.The results reveal that while testing with an ideal voltage source is cost-effective and convenient in the short term, it lacks the ability to capture the dynamic interactions and feedback loops of physical grid components.This limitation can obscure critical real world factors, potentially leading to unexpected inverter behavior and operational challenges in grids with high PV penetration.This study underscores the importance of re-evaluating conventional testing methods and incorporating Power Hardware in the Loop structures to achieve test results that more closely align with real-world conditions., Comment: 7 pages, 9 figures, study of behaviour of different inverters during different grid strength

The recent surge of building software systems powered by Large Language Models (LLMs) has led to the development of various testing frameworks, primarily focused on treating prompt templates as the unit of testing. Despite the significant costs associated with test input execution and output assessment, the curation of optimized test suites is yet overlooked in these tools, which calls for tailored test selection or prioritization strategies. In this paper, we show that diversity-based testing techniques, such as Adaptive Random Testing (ART) with appropriate string distance metrics, can be effectively applied to the testing of prompt templates. Our proposed adaptive testing approach adjusts the conventional ART process to this context by selecting new test inputs based on scores derived from existing test suite and their labelling results. Our results, obtained using various implementations that explore several string-based distances, confirm that our approach enables the discovery of failures with reduced testing budgets and promotes the generation of more varied outputs., Comment: 9 pages

Biological relation networks contain rich information for understanding the biological mechanisms behind the relationship of entities such as genes, proteins, diseases, and chemicals. The vast growth of biomedical literature poses significant challenges updating the network knowledge. The recent Biomedical Relation Extraction Dataset (BioRED) provides valuable manual annotations, facilitating the develop-ment of machine-learning and pre-trained language model approaches for automatically identifying novel document-level (inter-sentence context) relationships. Nonetheless, its annotations lack directionality (subject/object) for the entity roles, essential for studying complex biological networks. Herein we annotate the entity roles of the relationships in the BioRED corpus and subsequently propose a novel multi-task language model with soft-prompt learning to jointly identify the relationship, novel findings, and entity roles. Our results in-clude an enriched BioRED corpus with 10,864 directionality annotations. Moreover, our proposed method outperforms existing large language models such as the state-of-the-art GPT-4 and Llama-3 on two benchmarking tasks. Our source code and dataset are available at https://github.com/ncbi-nlp/BioREDirect.

The state-of-the-art in biometric recognition algorithms and operational systems has advanced quickly in recent years providing high accuracy and robustness in more challenging collection environments and consumer applications. However, the technology still suffers greatly when applied to non-conventional settings such as those seen when performing identification at extreme distances or from elevated cameras on buildings or mounted to UAVs. This paper summarizes an extension to the largest dataset currently focused on addressing these operational challenges, and describes its composition as well as methodologies of collection, curation, and annotation., Comment: 10 pages, 11 figures, 2 tables, submitted to CVPR

Extreme coronal line emitters (ECLEs) are a rare class of galaxy that exhibit strong, high-ionization iron coronal emission lines in their spectra. In some cases, these lines are transient and may be the result of tidal disruption event (TDEs). To test this connection, we calculate the rate of variable ECLEs (vECLEs) at redshift $\sim0.3$. We search for ECLEs in the Baryon Oscillation Spectroscopic Survey (BOSS) LOWZ sample and discover two candidate ECLEs. Using follow-up spectra from the Dark Energy Spectroscopic Instrument and Gemini Multi-Object Spectrograph, and mid-infrared observations from the Wide-field Infrared Survey Explorer, we determine that one of these galaxies is a vECLE. Using this galaxy, we calculate the galaxy-normalized vECLE rate at redshift $\sim0.3$ to be $R_\mathrm{G}=1.6~^{+3.8}_{-1.4}\times10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$ and the mass-normalized rate to be $R_\mathrm{M}=7~^{+16}_{-6}\times10^{-18}~\mathrm{M_\odot^{-1}}~\mathrm{yr}^{-1}$. This is then converted to a volumetric rate of $R_\mathrm{V}=1.8~^{+4.5}_{-1.5}\times10^{-9}~\mathrm{Mpc}^{-3}~\mathrm{yr}^{-1}$. Formally, the LOWZ vECLE rates are $2-4$ times lower than the rates calculated from the Sloan Digital Sky Survey Legacy sample at redshift $\sim0.1$. However, given the large uncertainties on both measurements, they are consistent with each other at $1\sigma$. Both the galaxy-normalized and volumetric rates are one to two orders of magnitude lower than TDE rates from the literature, consistent with vECLEs being caused by $5-20$ per cent of all TDEs., Comment: 15 pages, 10 figures. Submitted to MNRAS. arXiv admin note: text overlap with arXiv:2402.16951

We present an atmospheric characterization and orbital analysis of HD 206893 B, an exceptionally red, L/T-transition substellar companion in a multiplanetary system, via Keck Planet Imager and Characterizer (KPIC) high-resolution (R $\sim$ 35,000) K-band spectroscopy. Using PHOENIX atmospheric models in a forward-model framework that fits the spectrum of the companion and diffracted starlight simultaneously, we detect HD 206893 B at $>8\sigma$ significance via cross-correlation in two epochs. We find an effective temperature for the companion of $1634^{+72}_{-38}$ K and a log(g) of $4.55^{+0.17}_{-0.22}$. Only accounting for statistical uncertainties, we measure the carbon-oxygen ratio (C/O) of this companion to be $0.57 \pm 0.02$, or near-solar while assuming solar metallicity. The C/O ratio we measure fits the tentative trend of $>4 M_{Jup}$ companions having near-solar C/O ratios while less massive companions have greater-than-solar C/O ratios. Using substellar evolution models, we find an age of $112^{+36}_{-22}$ Myr, a mass of $22.7^{+2.5}_{-1.7} M_{Jup}$, and a radius of $1.11 \pm 0.03 R_{Jup}$ for this companion. We also use KPIC radial velocity data to fit the orbit of HD 206893 B and analyze the orbital stability of this system. We find that the orbital stability is relatively independent of the mass of HD 206893 B, and favors an orbital configuration where B and its interior planetary companion, HD 206893 c, are co-planar. The measured C/O ratio coupled with the current architecture of the system cannot rule out a core accretion scenario, nor a disk fragmentation scenario regarding the formation pathway of HD 206893 B., Comment: 37 pages, 23 figures

Advanced multimodal AI agents can now collaborate with users to solve challenges in the world. We explore eye tracking's role in such interaction to convey a user's attention relative to the physical environment. We hypothesize that this knowledge improves contextual understanding for AI agents. By observing hours of human-object interactions, we first measure the relationship between an eye tracker's signal quality and its ability to reliably place gaze on nearby physical objects. We then conduct experiments which relay the user's scanpath history as additional context querying multimodal agents. Our results show that eye tracking provides high value as a user attention signal and can convey information about the user's current task and interests to the agent.

Bosonic statistics give rise to remarkable phenomena, from the Hong-Ou-Mandel effect to Bose-Einstein condensation, with applications spanning fundamental science to quantum technologies. Modeling bosonic systems relies heavily on effective descriptions: typical examples include truncating their infinite-dimensional state space and restricting their dynamics to a simple class of Hamiltonians, such as polynomials of canonical operators, which are used to define quantum computing over bosonic modes. However, many natural bosonic Hamiltonians do not belong to this simple class, and some quantum effects harnessed by bosonic computers inherently require infinite-dimensional spaces, questioning the validity of such effective descriptions of bosonic systems. How can we trust results obtained with such simplifying assumptions to capture real effects? Driven by the increasing importance of bosonic systems for quantum technologies, we solve this outstanding problem by showing that these effective descriptions do in fact capture the relevant physics of bosonic systems. Our technical contribution is twofold: firstly, we prove that any physical, bosonic unitary evolution can be strongly approximated by a finite-dimensional unitary evolution; secondly, we show that any finite-dimensional unitary evolution can be generated exactly by a bosonic Hamiltonian that is a polynomial of canonical operators. Beyond their fundamental significance, our results have implications for classical and quantum simulations of bosonic systems, they provide universal methods for engineering bosonic quantum states and Hamiltonians, they show that polynomial Hamiltonians do generate universal gate sets for quantum computing over bosonic modes, and they lead to an infinite-dimensional Solovay--Kitaev theorem., Comment: 21 pages, comments welcome!

Successful operation of large particle detectors like the Compact Muon Solenoid (CMS) at the CERN Large Hadron Collider requires rapid, in-depth assessment of data quality. We introduce the ``AutoDQM'' system for Automated Data Quality Monitoring using advanced statistical techniques and unsupervised machine learning. Anomaly detection algorithms based on the beta-binomial probability function, principal component analysis, and neural network autoencoder image evaluation are tested on the full set of proton-proton collision data collected by CMS in 2022. AutoDQM identifies anomalous ``bad'' data affected by significant detector malfunction at a rate 4 -- 6 times higher than ``good'' data, demonstrating its effectiveness as a general data quality monitoring tool., Comment: 16 pages, 14 figures

Detecting weaknesses in cryptographic algorithms is of utmost importance for designing secure information systems. The state-of-the-art soft analytical side-channel attack (SASCA) uses physical leakage information to make probabilistic predictions about intermediate computations and combines these "guesses" with the known algorithmic logic to compute the posterior distribution over the key. This attack is commonly performed via loopy belief propagation, which, however, lacks guarantees in terms of convergence and inference quality. In this paper, we develop a fast and exact inference method for SASCA, denoted as ExSASCA, by leveraging knowledge compilation and tractable probabilistic circuits. When attacking the Advanced Encryption Standard (AES), the most widely used encryption algorithm to date, ExSASCA outperforms SASCA by more than 31% top-1 success rate absolute. By leveraging sparse belief messages, this performance is achieved with little more computational cost than SASCA, and about 3 orders of magnitude less than exact inference via exhaustive enumeration. Even with dense belief messages, ExSASCA still uses 6 times less computations than exhaustive inference., Comment: ICML 2024 Conference Paper

We reconsider various C-metric spacetimes describing charged and (slowly) accelerating AdS black holes in different theories of (non-linear) electrodynamics and revisit their thermodynamic properties. Focusing first on the Maxwell theory, we find a parametrization of the metric where we can eliminate the non-trivial `normalization' of the boost Killing vector which was crucial for obtaining consistent thermodynamics in previous studies. We also calculate the Euclidean action using i) the standard holographic renormalization and ii) using the topological renormalization, showing that in the presence of overall cosmic string tension the two do not agree. These results are also extended to accelerating black holes in ModMax and RegMax non-linear electrodynamics. Interestingly, for the latter the electrostatic potential picks up a modification, that remains to be explained, but is consistent with the topological renormalization and the (generalized) Hawking--Ross prescription. Our study indicates that thermodynamics of charged accelerating black holes is far from being completely understood.

Irregular codes are bottlenecked by memory and communication latency. Decoupled access/execute (DAE) is a common technique to tackle this problem. It relies on the compiler to separate memory address generation from the rest of the program, however, such a separation is not always possible due to control and data dependencies between the access and execute slices, resulting in a loss of decoupling. In this paper, we present compiler support for speculation in DAE architectures that preserves decoupling in the face of control dependencies. We speculate memory requests in the access slice and poison mis-speculations in the execute slice without the need for replays or synchronization. Our transformation works on arbitrary, reducible control flow and is proven to preserve sequential consistency. We show that our approach applies to a wide range of architectural work on CPU/GPU prefetchers, CGRAs, and accelerators, enabling DAE on a wider range of codes than before., Comment: To appear in the Proceedings of the 34th ACM SIGPLAN International Conference on Compiler Construction (CC 2025)

Quantum computing is an emerging technology that has seen significant software and hardware improvements in recent years. Executing a quantum program requires the compilation of its quantum circuit for a target Quantum Processing Unit (QPU). Various methods for qubit mapping, gate synthesis, and optimization of quantum circuits have been proposed and implemented in compilers. These compilers try to generate a quantum circuit that leads to the best execution quality - a criterion that is usually approximated by figures of merit such as the number of (two-qubit) gates, the circuit depth, expected fidelity, or estimated success probability. However, it is often unclear how well these figures of merit represent the actual execution quality on a QPU. In this work, we investigate the correlation between established figures of merit and actual execution quality on real machines - revealing that the correlation is weaker than anticipated and that more complex figures of merit are not necessarily more accurate. Motivated by this finding, we propose an improved figure of merit (based on a machine learning approach) that can be used to predict the expected execution quality of a quantum circuit for a chosen QPU without actually executing it. The employed machine learning model reveals the influence of various circuit features on generating high correlation scores. The proposed figure of merit demonstrates a strong correlation and outperforms all previous ones in a case study - achieving an average correlation improvement of 49%., Comment: 7 pages, 3 figures

This paper describes Meta's ACH system for mutation-guided LLM-based test generation. ACH generates relatively few mutants (aka simulated faults), compared to traditional mutation testing. Instead, it focuses on generating currently undetected faults that are specific to an issue of concern. From these currently uncaught faults, ACH generates tests that can catch them, thereby `killing' the mutants and consequently hardening the platform against regressions. We use privacy concerns to illustrate our approach, but ACH can harden code against {\em any} type of regression. In total, ACH was applied to 10,795 Android Kotlin classes in 7 software platforms deployed by Meta, from which it generated 9,095 mutants and 571 privacy-hardening test cases. ACH also deploys an LLM-based equivalent mutant detection agent that achieves a precision of 0.79 and a recall of 0.47 (rising to 0.95 and 0.96 with simple pre-processing). ACH was used by Messenger and WhatsApp test-a-thons where engineers accepted 73% of its tests, judging 36% to privacy relevant. We conclude that ACH hardens code against specific concerns and that, even when its tests do not directly tackle the specific concern, engineers find them useful for their other benefits., Comment: Submitted to FSE 2025 Industry Track

The unit group of the ring of integers of a number field, modulo torsion, is a lattice via the logarithmic Minkowski embedding. We examine the shape of this lattice, which we call the unit shape, within the family of prime degree $p$ number fields whose Galois closure has dihedral Galois group $D_p$ and a unique real embedding. In the case $p = 5$, we prove that the unit shapes lie on a single hypercycle on the modular surface (in this case, the modular surface is the space of shapes of rank $2$ lattices). For general $p$, we show that the unit shapes are contained in a finite union of translates of periodic torus orbits in the space of shapes., Comment: Comments welcome!

Prostate cancer (PCa) detection using deep learning (DL) models has shown potential for enhancing real-time guidance during biopsies. However, prostate ultrasound images lack pixel-level cancer annotations, introducing label noise. Current approaches often focus on limited regions of interest (ROIs), disregarding anatomical context necessary for accurate diagnosis. Foundation models can overcome this limitation by analyzing entire images to capture global spatial relationships; however, they still encounter challenges stemming from the weak labels associated with coarse pathology annotations in ultrasound data. We introduce Cinepro, a novel framework that strengthens foundation models' ability to localize PCa in ultrasound cineloops. Cinepro adapts robust training by integrating the proportion of cancer tissue reported by pathology in a biopsy core into its loss function to address label noise, providing a more nuanced supervision. Additionally, it leverages temporal data across multiple frames to apply robust augmentations, enhancing the model's ability to learn stable cancer-related features. Cinepro demonstrates superior performance on a multi-center prostate ultrasound dataset, achieving an AUROC of 77.1% and a balanced accuracy of 83.8%, surpassing current benchmarks. These findings underscore Cinepro's promise in advancing foundation models for weakly labeled ultrasound data., Comment: accepted to IEEE ISBI 2025

Consider the problem of deciding, for a particular multipartite quantum state, whether or not it is realizable in a quantum network with a particular causal structure. This is a fully quantum version of what causal inference researchers refer to as the problem of causal discovery. In this work, we introduce a fully quantum version of the inflation technique for causal inference, which leverages the quantum marginal problem. We illustrate the utility of this method using a simple example: testing compatibility of tripartite quantum states with the quantum network known as the triangle scenario. We show, in particular, how the method yields a complete classification of pure three-qubit states into those that are and those that are not compatible with the triangle scenario. We also provide some illustrative examples involving mixed states and some where one or more of the systems is higher-dimensional. Finally, we examine the question of when the incompatibility of a multipartite quantum state with a causal structure can be inferred from the incompatibility of a joint probability distribution induced by implementing measurements on each subsystem., Comment: 20+6 pages; 3 figures