Search

Despite increasing recognition of the importance of high-quality school leadership, we know remarkably little about principal skill development. Using administrative data from Tennessee, Oregon, and New York City, we estimate the returns to principal experience as measured by student outcomes, teacher hiring and retention patterns, and teacher and supervisor ratings of principals. The typical principal leads a school for only 3-5 years and leaves the principalship after 6-7 years. We find little evidence that school performance improves as principals gain experience, despite substantial improvement in supervisor ratings. Our results suggest that strategies intended to increase principal retention are unlikely to improve school outcomes absent more comprehensive efforts to strengthen the link between principal skill development and student and school outcomes.

The physics of recombination lines (RLs) in the HeI singlet system is expected to be relatively simple, supported by accurate atomic models. We examine the intensities of HeI singlets $\lambda \lambda$3614, 3965, 5016, 6678, 7281 and the triplet HeI $\lambda$5876 in various types of ionized nebulae and compare them with theoretical predictions to test the validity of the ``Case B'' recombination scenario and the assumption of thermal homogeneity. Our analysis includes 85 spectra from Galactic and extragalactic HII regions, 90 from star-forming galaxies, and 218 planetary nebulae, all compiled by the DEep Spectra of Ionized REgions Database Extended (DESIRED-E) project. By evaluating the ratios HeI $\lambda$7281/$\lambda$6678 and HeI $\lambda$7281/$\lambda$5876, we determine $T_e$(HeI) and compare it with direct measurements of $T_e$([OIII] $\lambda$4363/$\lambda$5007). We find that $T_e$(HeI) is systematically lower than $T_e$([OIII]) across most objects and nebula types. Additionally, we identify a correlation between the abundance discrepancy factor (ADF(O$^{2+}$)) and the difference $T_e$([OIII]) - $T_e$(HeI) for planetary nebulae. We explore two potential explanations: photon loss from $n^1P \rightarrow 1^1S$ transitions and temperature inhomogeneities. Deviations from ``Case B'' may indicate photon absorption by HI rather than HeI and/or generalized ionizing photon escape, highlighting the need for detailed consideration of radiative transfer effects. If temperature inhomogeneities are widespread, identifying a common physical phenomenon affecting all ionized nebulae is crucial. Our results suggest that both scenarios can contribute to the observed discrepancies., Comment: Submitted to the AAS, comments and feedback from the community are welcome

The propagation of wave fields and their interactions with matter are important for established and emerging fields in optical sciences. Efficient methods for predicting such behaviour have been employed routinely for coherent sources. However, most real world optical systems exhibit partial coherence, for which the present mathematical description involves high dimensional complex functions and hence poses challenges for numerical implementations. This demands significant computational resources to determine the properties of partially coherent wavefields. Here, we describe the novel Phase-Space (PS) propagator, an efficient and self-consistent technique for free space propagation of wave fields which are partially coherent in the spatial domain. The PS propagator makes use of the fact that the propagation of a wave field in free space is equivalent to a shearing of the corresponding PSD function. Computationally, this approach is simpler and the need for using different propagation methods for near and far-field regions is removed., Comment: 17 pages, 4 figures, to be submitted to Optics Communications For the associated Python package, see https://github.com/jakerogers-1/Phase-Space-Propagator

Accurate forest canopy height estimation is essential for evaluating aboveground biomass and carbon stock dynamics, supporting ecosystem monitoring services like timber provisioning, climate change mitigation, and biodiversity conservation. However, despite advancements in spaceborne LiDAR technology, data for northern high latitudes remain limited due to orbital and sampling constraints. This study introduces a methodology for generating spatially continuous, high-resolution canopy height and uncertainty estimates using Deep Learning Regression models. We integrate multi-source, multi-seasonal satellite data from Sentinel-1, Landsat, and ALOS-PALSAR-2, with spaceborne GEDI LiDAR as reference data. Our approach was tested in Ontario, Canada, and validated with airborne LiDAR, demonstrating strong performance. The best results were achieved by incorporating seasonal Sentinel-1 and Landsat features alongside PALSAR data, yielding an R-square of 0.72, RMSE of 3.43 m, and bias of 2.44 m. Using seasonal data instead of summer-only data improved variability by 10%, reduced error by 0.45 m, and decreased bias by 1 m. The deep learning model's weighting strategy notably reduced errors in tall canopy height estimates compared to a recent global model, though it overestimated lower canopy heights. Uncertainty maps highlighted greater uncertainty near forest edges, where GEDI measurements are prone to errors and SAR data may encounter backscatter issues like foreshortening, layover, and shadow. This study enhances canopy height estimation techniques in areas lacking spaceborne LiDAR coverage, providing essential tools for forestry, environmental monitoring, and carbon stock estimation.

This paper presents a divergence cleaning formulation for the velocity in the weakly compressible smoothed particle hydrodynamics (SPH) scheme. The proposed hyperbolic/parabolic divergence cleaning, ensures that the velocity divergence, $div(\mathbf{u})$, is minimised throughout the simulation. The divergence equation is coupled with the momentum conservation equation through a scalar field $\psi$. A parabolic term is added to the time-evolving divergence equation, resulting in a hyperbolic/parabolic form, dissipating acoustic waves with a speed of sound proportional to the local Mach number in order to maximise dissipation of the velocity divergence, preventing unwanted diffusion of the pressure field. The $div(\mathbf{u})$-SPH algorithm is implemented in the open-source weakly compressible SPH solver DualSPHysics. The new formulation is validated against a range of challenging 2-D test cases including the Taylor-Green vortices, patch impact test, jet impinging on a surface, and wave impact in a sloshing tank. The results show that the new formulation reduces the divergence in the velocity field by at least one order of magnitude which prevents spurious numerical noise and the formation of unphysical voids. The temporal evolution of the impact pressures shows that the $div(\mathbf{u})$-SPH formulation virtually eliminates unwanted acoustic pressure oscillations. Investigation of particle resolution confirms that the new $div(\mathbf{u})$-SPH formulation does not reduce the spatial convergence rate.

HIP 41378 f is a sub-Neptune exoplanet with an anomalously low density. Its long orbital period and deep transit make it an ideal candidate for detecting oblateness photometrically. We present a new cross-platform, GPU-enabled code greenlantern, suitable for computing transit light curves of oblate planets at arbitrary orientations. We then use Markov Chain Monte Carlo to fit K2 data of HIP 41378 b, d, and f, specifically examining HIP 41378 f for possible oblateness and obliquity. We find that the flattening of HIP 41378 f is $f \leq 0.18$ at the 95% confidence level, consistent with a rotation period of $P_\text{rot} \geq 22.2$ hr. In the future, high-precision data from JWST has the potential to tighten such a constraint and can differentiate between spherical and flattened planets., Comment: 14 pages, 10 figures, 2 tables. Submitted to ApJL. Code available at https://github.com/emprice/greenlantern

As a step towards the ultimate goal of a high-precision mass measurement of doubly-magic $^{100}$Sn, the mass of $^{103}$Sn was measured at the Low Energy Beam and Ion Trap (LEBIT) located at the Facility for Rare Isotope Beams (FRIB). Utilizing the time-of-flight ion cyclotron resonance (ToF-ICR) technique, a mass uncertainty of 3.7~keV was achieved, an improvement by more than an order of magnitude compared to a recent measurement performed in 2023 at the Cooler Storage Ring (CSRe) in Lanzhou. Although the LEBIT and CSRe mass measurements of $^{103}$Sn are in agreement, they diverge from the experimental mass value reported in the 2016 version of the Atomic Mass Evaluation (AME2016), which was derived from the measured $Q_{\beta^+}$ value and the mass of $^{103}$In. In AME2020, this indirectly measured $^{103}$Sn mass was classified as a `seriously irregular mass' and replaced with an extrapolated value, which aligns with the most recent measured values from CSRe and LEBIT. As such, the smoothness of the mass surface is confidently reestablished for $^{103}$Sn. Furthermore, LEBIT's mass measurement of $^{103}$Sn enabled a significant reduction in the mass uncertainties of five parent isotopes which are now dominated by uncertainties in their respective $Q$-values.

Super-Earths are highly irradiated, small planets with bulk densities approximately consistent with Earth. We construct combined interior-atmosphere models of super-Earths that trace the partitioning of water throughout a planet, including an iron-rich core, silicate-rich mantle, and steam atmosphere. We compare these models with exoplanet observations to infer a $1\sigma$ upper limit on total water mass fraction of $\lesssim 3\%$ at the population level. We consider end-member scenarios that may change this value, including the efficiency of mantle outgassing and escape of high mean-molecular weight atmospheres. Although our constraints are agnostic as to the origin of water, we show that our upper limits are consistent with its production via chemical reactions of primordial hydrogen-dominated atmospheres with magma oceans. This mechanism has also been hypothesised to explain Earth's water content, possibly pointing to a unified channel for the origins of water on small terrestrial planets., Comment: Submitted to ApJ

Precision spraying evaluation requires automation primarily in post-spraying imagery. In this paper we propose an eXplainable Artificial Intelligence (XAI) computer vision pipeline to evaluate a precision spraying system post-spraying without the need for traditional agricultural methods. The developed system can semantically segment potential targets such as lettuce, chickweed, and meadowgrass and correctly identify if targets have been sprayed. Furthermore, this pipeline evaluates using a domain-specific Weakly Supervised Deposition Estimation task, allowing for class-specific quantification of spray deposit weights in {\mu}L. Estimation of coverage rates of spray deposition in a class-wise manner allows for further understanding of effectiveness of precision spraying systems. Our study evaluates different Class Activation Mapping techniques, namely AblationCAM and ScoreCAM, to determine which is more effective and interpretable for these tasks. In the pipeline, inference-only feature fusion is used to allow for further interpretability and to enable the automation of precision spraying evaluation post-spray. Our findings indicate that a Fully Convolutional Network with an EfficientNet-B0 backbone and inference-only feature fusion achieves an average absolute difference in deposition values of 156.8 {\mu}L across three classes in our test set. The dataset curated in this paper is publicly available at https://github.com/Harry-Rogers/PSIE

Motivated by its application in the frequency assignment problem for cellular networks, conflict-free coloring was first studied by Even et al. in [Conflict-free colorings of simple geometric regions with applications to frequency assignment in cellular networks, SIAM Journal on Computing, 2004]. A \emph{conflict-free coloring} of a hypergraph $\mathcal{H}$ is an assignment of colors to the vertex set of $\mathcal{H}$ such that every hyperedge in $\mathcal{H}$ has a vertex whose color is distinct from every other vertex in that hyperedge. The minimum number of colors required for such a coloring is known as the \emph{conflict-free chromatic number} of $\mathcal{H}$. Conflict-free coloring has also been studied on open/closed neighborhood hypergraphs of a given graph. In this paper, we study the list variant of conflict-free coloring where, for every vertex $v$, we are given a list of admissible colors $L_v$ such that $v$ is allowed to be colored only from $L_v$. We prove upper bounds for the list conflict-free chromatic number of general hypergraphs and graphs., Comment: 17 pages

We present ConvexECG, an explainable and resource-efficient method for reconstructing six-lead electrocardiograms (ECG) from single-lead data, aimed at advancing personalized and continuous cardiac monitoring. ConvexECG leverages a convex reformulation of a two-layer ReLU neural network, enabling the potential for efficient training and deployment in resource constrained environments, while also having deterministic and explainable behavior. Using data from 25 patients, we demonstrate that ConvexECG achieves accuracy comparable to larger neural networks while significantly reducing computational overhead, highlighting its potential for real-time, low-resource monitoring applications.

Classification models are a key component of structural digital twin technologies used for supporting asset management decision-making. An important consideration when developing classification models is the dimensionality of the input, or feature space, used. If the dimensionality is too high, then the `curse of dimensionality' may rear its ugly head; manifesting as reduced predictive performance. To mitigate such effects, practitioners can employ dimensionality reduction techniques. The current paper formulates a decision-theoretic approach to dimensionality reduction for structural asset management. In this approach, the aim is to keep incurred misclassification costs to a minimum, as the dimensionality is reduced and discriminatory information may be lost. This formulation is constructed as an eigenvalue problem, with separabilities between classes weighted according to the cost of misclassifying them when considered in the context of a decision process. The approach is demonstrated using a synthetic case study., Comment: To appear in the Proceedings of ISMA 2024 (International Conference on Noise and Vibration Engineering) and USD2024 (International Conference on Uncertainty in Structural Dynamics), Leuven, Belgium

Over the Nullarbor Plain in South Australia, the Desert Fireball Network detected a fireball on the night of 1 June 2019 (7:30 pm local time), and six weeks later recovered a single meteorite (42 g) named Arpu Kuilpu. This meteorite was then distributed to a consortium of collaborating institutions to be measured and analyzed by a number of methodologies including: SEM-EDS, EPMA, ICP-MS, gamma-ray spectrometry, ideal gas pycnometry, magnetic susceptibility measurement, {\mu}CT, optical microscopy, and accelerator and noble gas mass spectrometry techniques. These analyses revealed that Arpu Kuilpu is an unbrecciated H5 ordinary chondrite, with minimal weathering (W0-1) and minimal shock (S2). The olivine and pyroxene mineral compositions (in mol%) are Fa: 19.2 +- 0.2, and Fs: 16.8 +- 0.2, further supporting the H5 type and class. The measured oxygen isotopes are also consistent with an H chondrite ({\delta}17O = 2.904 +- 0.177; {\delta}18O = 4.163 +- 0.336; {\Delta}17O = 0.740 +- 0.002). Ideal gas pycnometry measured bulk and grain densities of 3.66 +- 0.02 and 3.77 +- 0.02 g cm-3, respectively, yielding a porosity of 3.0 % +- 0.7. The magnetic susceptibility of this meteorite is log X = 5.16 +- 0.08. The most recent impact-related heating event experienced by Arpu Kuilpu was measured by 40Ar/39Ar chronology to be 4467 +- 16 Ma, while the cosmic ray exposure age is estimated to be between 6-8 Ma. The noble gas isotopes, radionuclides, and fireball observations all indicate that Arpu Kuilpu's meteoroid was quite small (maximum radius of 10 cm, though more likely between 1-5 cm). Although this meteorite is a rather ordinary ordinary chondrite, its prior orbit resembled that of a Jupiter Family Comet (JFC) further lending support to the assertion that many cm- to m-sized objects on JFC orbits are asteroidal rather than cometary in origin.

Nearly thirty years after its inception, the field of DNA-programmed colloidal self-assembly has begun to realize its initial promise. In this review, we summarize recent developments in designing effective interactions and understanding the dynamic self-assembly pathways of DNA-coated nanoparticles and microparticles, as well as how these advances have propelled tremendous progress in crystal engineering. We also highlight exciting new directions showing that new classes of subunits combining nanoparticles with DNA origami can be used to engineer novel multicomponent assemblies, including structures with self-limiting, finite sizes. We conclude by providing an outlook on how recent theoretical advances focusing on the kinetics of self-assembly could usher in new materials-design opportunities, like the possibility of retrieving multiple distinct target structures from a single suspension or accessing new classes of materials that are stabilized by energy dissipation, mimicking self-assembly in living systems.

We prove Lie's Third Theorem for Lie $\infty$-algebras: Every finite-type, homologically and non-negatively graded $L_\infty$-algebra over $\mathbb{R}$ integrates to a finite-dimensional Lie $\infty$-group., Comment: 88 pages. Comments welcome

This article documents an open-source hardware ray tracer datapath pipeline module implemented with the Chisel hardware construction language. The module implements a unified fix-latency pipeline for Ray-Box and Ray-Triangle intersection tests which are the two core, compute-intensive tasks involved in Ray Tracing workloads. Furthermore, the module offers the flexibility of supporting two additional compute modes that can accelerate the computation of Euclidean distance and angular distance (aka cosine similarity) between two vectors, at the cost of minimal additional hardware overhead. Several design choices are made in favor of creating a composable and easily-modifiable Chisel module. This document also explains the trade-offs of these choices.

AI fairness measurements, including tests for equal treatment, often take the form of disaggregated evaluations of AI systems. Such measurements are an important part of Responsible AI operations. These measurements compare system performance across demographic groups or sub-populations and typically require member-level demographic signals such as gender, race, ethnicity, and location. However, sensitive member-level demographic attributes like race and ethnicity can be challenging to obtain and use due to platform choices, legal constraints, and cultural norms. In this paper, we focus on the task of enabling AI fairness measurements on race/ethnicity for \emph{U.S. LinkedIn members} in a privacy-preserving manner. We present the Privacy-Preserving Probabilistic Race/Ethnicity Estimation (PPRE) method for performing this task. PPRE combines the Bayesian Improved Surname Geocoding (BISG) model, a sparse LinkedIn survey sample of self-reported demographics, and privacy-enhancing technologies like secure two-party computation and differential privacy to enable meaningful fairness measurements while preserving member privacy. We provide details of the PPRE method and its privacy guarantees. We then illustrate sample measurement operations. We conclude with a review of open research and engineering challenges for expanding our privacy-preserving fairness measurement capabilities., Comment: Saikrishna Badrinarayanan and Osonde Osoba contributed equally to this work. Updating text to indicate limitations of sample analyses

Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applications (e.g.\ structural health monitoring), feature-label pairs used to learn such mappings are of limited availability which hinders the effectiveness of traditional supervised machine learning approaches. The current paper proposes a methodology for overcoming the issue of data scarcity by combining active learning with hierarchical Bayesian modelling. Active learning is an approach for preferentially acquiring feature-label pairs in a resource-efficient manner. In particular, the current work adopts a risk-informed approach that leverages contextual information associated with regression-based engineering decision-making tasks (e.g.\ inspection and maintenance). Hierarchical Bayesian modelling allow multiple related regression tasks to be learned over a population, capturing local and global effects. The information sharing facilitated by this modelling approach means that information acquired for one engineering system can improve predictive performance across the population. The proposed methodology is demonstrated using an experimental case study. Specifically, multiple regressions are performed over a population of machining tools, where the quantity of interest is the surface roughness of the workpieces. An inspection and maintenance decision process is defined using these regression tasks which is in turn used to construct the active-learning algorithm. The novel methodology proposed is benchmarked against an uninformed approach to label acquisition and independent modelling of the regression tasks. It is shown that the proposed approach has superior performance in terms of expected cost -- maintaining predictive performance while reducing the number of inspections required., Comment: 19 pages, 12 figures, 3 tables, submitted to Data-Centric Engineering

With the decreasing cost of consumer display technologies making it easier for universities to have larger displays in classrooms, and the ubiquitous use of online tools such as collaborative whiteboards for remote learning during the COVID-19 pandemic, combining the two can be useful in higher education. This is especially true in visually intensive classes, such as data visualization courses, that can benefit from additional "space to teach," coined after the "space to think" sense-making idiom. In this paper, we reflect on our approach to using SAGE3, a collaborative whiteboard with advanced features, in higher education to teach visually intensive classes, provide examples of activities from our own visually-intensive courses, and present student feedback. We gather our observations into usage patterns for using content-rich canvases in education., Comment: To be published in the EDUVIS workshop at IEEE VIS 2024

Attaching enzymes to nanostructures has proven useful to the study of enzyme functionality under controlled conditions and has led to new technologies. Often, the utility and interest of enzyme-tethered nanostructures lie in how the enzymatic activity is affected by how the enzymes are arranged in space. Therefore, being able to conjugate enzymes to nanostructures while preserving the enzymatic activity is essential. In this paper, we present a method to conjugate single-stranded DNA to the enzyme urease while maintaining enzymatic activity. We show evidence of successful conjugation and quantify the variables that affect the conjugation yield. We also show that the enzymatic activity is unchanged after conjugation compared to the enzyme in its native state. Finally, we demonstrate the tethering of urease to nanostructures made using DNA origami with high site-specificity. Decorating nanostructures with enzymatically-active urease may prove to be useful in studying, or even utilizing, the functionality of urease in disciplines ranging from biotechnology to soft-matter physics. The techniques we present in this paper will enable researchers across these fields to modify enzymes without disrupting their functionality, thus allowing for more insightful studies into their behavior and utility., Comment: 17 pages, 5 figures, SI is 2 pages

The muon collider has the potential to be a powerful tool for the exploration of frontiers in particle physics. In order to reach high luminosity, the 6D emittance of the muon beam needs to be reduced by several orders of magnitude. The cooling process for a muon collider involves two parts; initial six-dimensional cooling and final transverse cooling. This paper focuses on the former and proposes a conceptual design of the rectilinear cooling channel with additional dipole magnets. In this paper, we first introduce a general method for designing the rectilinear cooling channel. Subsequently, we apply this method to develop two rectilinear cooling channels before and after a bunch merging system. Furthermore, we investigate the impact on cooling performance by employing $\pi$-mode RF cavities and considering the effect of errors in the magnetic and RF fields.

The rapid increase in resident space objects, including satellites and orbital debris, threatens the safety and sustainability of space missions. This paper explores orbital debris remediation using laser ablation with a network of collaborative space-based lasers. A novel delta-v vector analysis framework quantifies the effects of multiple simultaneous laser-to-debris (L2D) engagements by leveraging a vector composition of imparted delta-v vectors. The paper introduces the Concurrent Location-Scheduling Problem (CLSP), which optimizes the placement of laser platforms and schedules L2D engagements to maximize debris remediation capacity. Due to the computational complexity of CLSP, it is decomposed into two sequential subproblems: (1) optimal laser platform locations are determined using the Maximal Covering Location Problem, and (2) a novel integer linear programming-based approach schedules L2D engagements within the network configuration to maximize remediation capacity. Computational experiments are conducted to evaluate the proposed framework's effectiveness under various mission scenarios, demonstrating key network functions such as collaborative nudging, deorbiting, and just-in-time collision avoidance. A cost-benefit analysis further explores how varying the number and distribution of laser platforms affects debris remediation capacity, providing insights into optimizing the performance of space-based laser networks., Comment: 41 pages, 13 figures, submitted to the Journal of Spacecraft and Rockets

This report highlights the findings of the sixteenth survey of states conducted by the National Center on Educational Outcomes (NCEO). It has been administered for more than three decades to collect information from states about the participation and performance of students with disabilities in the assessments that comprise the comprehensive assessment system. Topics addressed included: accessibility and accommodations, alternate assessments based on alternate academic achievement standards (AA-AAAS), interim assessments, accountability, English learners with disabilities, technology, graduation requirements, State Systemic Improvement Plans (SSIPs)/State-identified Measurable Results (SiMRs), family engagement, and technical assistance needs.

This is the third in a series of annual reports about teacher shortages in Michigan that the state legislature requested in December 2020 (2020 PA 316). Although the state data on this topic is limited, these analyses still help to paint a picture of teacher shortages across Michigan, assist policymakers to target policies and programs in ways that can best support the state and local communities in growing their teacher workforces, and highlight ways that new or better data may provide a deeper understanding of local and statewide teacher shortages. In addition to updating the analyses from EPIC's first comprehensive report, we continue to adjust and expand on our past analyses based on the results from prior reports and any additions or improvements to the data available each year.

A multiplicatively idempotent rig (which we abbreviate to mirig) is a rig satisfying the equation $r^2 = r$. We show that a free mirig on finitely many generators is finite and compute its size. This work was originally motivated by a collaborative effort on the decentralized social network Mastodon to compute the size of the free mirig on two generators., Comment: 38 pages, of which 3 are landscape

Future information processing technologies like quantum memory devices have the potential to store and transfer quantum states to enable quantum computing and networking. A central consideration in practical applications for such devices is the nature of the light-matter interface which determines the storage state density and efficiency. Here, we employ an organic radical, $\alpha$,$\gamma$-bisdiphenylene-$\beta$-phenylallyl (BDPA) doped into an o-terphenyl host to explore the potential for using tuneable and high-performance molecular media in microwave-based quantum applications. We demonstrate that this radical system exhibits millisecond-long spin-lattice relaxation and microsecond-long phase memory times at room temperature, while also having the capability to generate an oscillating spin-polarized state using a co-dissolved photo-activated tetraphenylporphyrin moiety, all enabled by using a viscous liquid host. This latest system builds upon collective wisdom from previous molecules-for-quantum literature by combining careful host matrix selection, with dynamical decoupling, and photoexcited triplet-radical spin polarisation to realise a versatile and robust quantum spin medium.

DarkSide-20k (DS-20k) is a dark matter detection experiment under construction at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It utilises ~100 t of low radioactivity argon from an underground source (UAr) in its inner detector, with half serving as target in a dual-phase time projection chamber (TPC). The UAr cryogenics system must maintain stable thermodynamic conditions throughout the experiment's lifetime of >10 years. Continuous removal of impurities and radon from the UAr is essential for maximising signal yield and mitigating background. We are developing an efficient and powerful cryogenics system with a gas purification loop with a target circulation rate of 1000 slpm. Central to its design is a condenser operated with liquid nitrogen which is paired with a gas heat exchanger cascade, delivering a combined cooling power of >8 kW. Here we present the design choices in view of the DS-20k requirements, in particular the condenser's working principle and the cooling control, and we show test results obtained with a dedicated benchmarking platform at CERN and LNGS. We find that the thermal efficiency of the recirculation loop, defined in terms of nitrogen consumption per argon flow rate, is 95 % and the pressure in the test cryostat can be maintained within $\pm$(0.1-0.2) mbar. We further detail a 5-day cool-down procedure of the test cryostat, maintaining a cooling rate typically within -2 K/h, as required for the DS-20k inner detector. Additionally, we assess the circuit's flow resistance, and the heat transfer capabilities of two heat exchanger geometries for argon phase change, used to provide gas for recirculation. We conclude by discussing how our findings influence the finalisation of the system design, including necessary modifications to meet requirements and ongoing testing activities., Comment: 45 pages, 24 figures

We investigate the consequences of non-ideal chemical interaction between silicate and overlying hydrogen-rich envelopes for rocky planets using basic tenets of phase equilibria. Based on our current understanding of the temperature and pressure conditions for complete miscibility of silicate and hydrogen, we find that the silicate-hydrogen binary solvus will dictate the nature of atmospheres and internal layering in rocky planets that garnered H$_2$-rich primary atmospheres. The temperatures at the surfaces of supercritical magma oceans will correspond to the silicate-hydrogen solvus. As a result, the radial positions of supercritical magma ocean-atmosphere interfaces, rather than their temperatures and pressures, should reflect the thermal states of these planets. The conditions prescribed by the solvus influence the structure of the atmosphere, and thus the transit radii of sub-Neptunes. Separation of iron-rich metal to form metal cores in sub-Neptunes and super-Earths is not assured due to prospects for neutral buoyancy of metal in silicate melt induced by dissolution of H, Si, and O in the metal at high temperatures., Comment: 13 figures, in review for PSJ, fixed typo in Eqn 24

The CHIPS R&D project focuses on development of low-cost water Cherenkov neutrino detectors through novel design strategies and resourceful engineering. This work presents an end-to-end DAQ solution intended for a recent 5 kt CHIPS prototype, which is largely based on affordable mass-produced components. Much like the detector itself, the presented instrumentation is composed of modular arrays that can be scaled up and easily serviced. A single such array can carry up to 30 photomultiplier tubes (PMTs) accompanied by electronics that generate high voltage in-situ and deliver time resolution of up to 0.69 ns. In addition, the technology is compatible with the White Rabbit timing system, which can synchronize its elements to within 100 ps. While deployment issues did not permit the presented DAQ system to operate beyond initial evaluation, the presented hardware and software successfully passed numerous commissioning tests that demonstrated their viability for use in a large-scale neutrino detector, instrumented with thousands of PMTs., Comment: 30 pages, 28 figures, submitted to MDPI Applied Sciences, Special Issue: Advanced Neutrino Detector Development and Application

This paper introduces an intelligent lecturing assistant (ILA) system that utilizes a knowledge graph to represent course content and optimal pedagogical strategies. The system is designed to support instructors in enhancing student learning through real-time analysis of voice, content, and teaching methods. As an initial investigation, we present a case study on lecture voice sentiment analysis, in which we developed a training set comprising over 3,000 one-minute lecture voice clips. Each clip was manually labeled as either engaging or non-engaging. Utilizing this dataset, we constructed and evaluated several classification models based on a variety of features extracted from the voice clips. The results demonstrate promising performance, achieving an F1-score of 90% for boring lectures on an independent set of over 800 test voice clips. This case study lays the groundwork for the development of a more sophisticated model that will integrate content analysis and pedagogical practices. Our ultimate goal is to aid instructors in teaching more engagingly and effectively by leveraging modern artificial intelligence techniques.

In the field of operational modal analysis (OMA), obtained modal information is frequently used to assess the current state of aerospace, mechanical, offshore and civil structures. However, the stochasticity of operational systems and the lack of forcing information can lead to inconsistent results. Quantifying the uncertainty of the recovered modal parameters through OMA is therefore of significant value. In this article, a new perspective on Bayesian OMA is proposed: a Bayesian stochastic subspace identification (SSI) algorithm. Distinct from existing approaches to Bayesian OMA, a hierarchical probabilistic model is embedded at the core of covariance-driven SSI. Through substitution of canonical correlation analysis with a Bayesian equivalent, posterior distributions over the modal properties are obtained. Two inference schemes are presented for the proposed Bayesian formulation: Markov Chain Monte Carlo and variational Bayes. Two case studies are then explored. The first is benchmark study using data from a simulated, multi degree-of-freedom, linear system. Following application of Bayesian SSI, it is shown that the same posterior is targeted and recovered by both inference schemes, with good agreement between the posterior mean and the conventional SSI result. The second study applies the variational form to data obtained from an in-service structure: The Z24 bridge. The results of this study are presented at single model orders, and then using a stabilisation diagram. The recovered posterior uncertainty is presented and compared to the classic SSI result. It is observed that the posterior distributions with mean values coinciding with the natural frequencies exhibit lower variance than values situated away from the natural frequencies.

Model parsimony is an important \emph{cognitive bias} in data-driven modelling that aids interpretability and helps to prevent over-fitting. Sparse identification of nonlinear dynamics (SINDy) methods are able to learn sparse representations of complex dynamics directly from data, given a basis of library functions. In this work, a novel Bayesian treatment of dictionary learning system identification, as an alternative to SINDy, is envisaged. The proposed method -- Bayesian identification of nonlinear dynamics (BINDy) -- is distinct from previous approaches in that it targets the full joint posterior distribution over both the terms in the library and their parameterisation in the model. This formulation confers the advantage that an arbitrary prior may be placed over the model structure to produce models that are sparse in the model space rather than in parameter space. Because this posterior is defined over parameter vectors that can change in dimension, the inference cannot be performed by standard techniques. Instead, a Gibbs sampler based on reversible-jump Markov-chain Monte-Carlo is proposed. BINDy is shown to compare favourably to ensemble SINDy in three benchmark case-studies. In particular, it is seen that the proposed method is better able to assign high probability to correct model terms.

This talk summarized work done recently to organize the steps for implementing TMD phenomenology in a way optimized for contexts where the extraction and interpretation of hadronic structures and nonperturbative effects is the primary driving motivation., Comment: 17 pages, proceedings of 7th International Workshop on Transverse phenomena in hard processes and the transverse structure of the proton (Transversity2024)

Detecting flying animals (e.g., birds, bats, and insects) using weather radar helps gain insights into animal movement and migration patterns, aids in management efforts (such as biosecurity) and enhances our understanding of the ecosystem.The conventional approach to detecting animals in weather radar involves thresholding: defining and applying thresholds for the radar variables, based on expert opinion. More recently, Deep Learning approaches have been shown to provide improved performance in detection. However, obtaining sufficient labelled weather radar data for flying animals to build learning-based models is time-consuming and labor-intensive. To address the challenge of data labelling, we propose a self-supervised learning method for detecting animal movement. In our proposed method, we pre-train our model on a large dataset with noisy labels produced by a threshold approach. The key advantage is that the pre-trained dataset size is limited only by the number of radar images available. We then fine-tune the model on a small human-labelled dataset. Our experiments on Australian weather radar data for waterbird segmentation show that the proposed method outperforms the current state-of-the art approach by 43.53% in the dice co-efficient statistic.

HIP94235 b, a 120 Myr old sub-Neptune, provides us the unique opportunity to study mass loss at a pivotal stage of the system's evolution: the end of a 100 million year (Myr) old phase of intense XUV irradiation. We present two observations of HIP94235 b using the Hubble Space Telescope's Space Telescope Imaging Spectrograph (HST/STIS) in the Ly-alpha wavelength region. We do not observe discernible differences across either the blue and red wings of the Ly-alpha line profile in and out of transit, and report no significant detection of outflowing neutral hydrogen around the planet. We constrain the rate of neutral hydrogen escaping HIP94235 b to an upper limit of 10^13 g/s, which remains consistent with energy-limited model predictions of 10^11 g/s. The Ly-alpha non-detection is likely due to the extremely short photoionization timescale of the neutral hydrogen escaping the planet's atmosphere. This timescale, approximately 15 minutes, is significantly shorter than that of any other planets with STIS observations. Through energy-limited mass loss models, we anticipate that HIP94235 b will transition into a super-Earth within a timescale of 1 Gyr., Comment: Accepted for publication in AJ

When faced with a new customer, many factors contribute to an insurance firm's decision of what offer to make to that customer. In addition to the expected cost of providing the insurance, the firm must consider the other offers likely to be made to the customer, and how sensitive the customer is to differences in price. Moreover, firms often target a specific portfolio of customers that could depend on, e.g., age, location, and occupation. Given such a target portfolio, firms may choose to modulate an individual customer's offer based on whether the firm desires the customer within their portfolio. We term the problem of modulating offers to achieve a desired target portfolio the portfolio pursuit problem. Having formulated the portfolio pursuit problem as a sequential decision making problem, we devise a novel reinforcement learning algorithm for its solution. We test our method on a complex synthetic market environment, and demonstrate that it outperforms a baseline method which mimics current industry approaches to portfolio pursuit., Comment: 16 pages, 1 figure

TOI-6255~b (GJ 4256) is an Earth-sized planet (1.079$\pm0.065$ $R_\oplus$) with an orbital period of only 5.7 hours. With the newly commissioned Keck Planet Finder (KPF) and CARMENES spectrographs, we determined the planet's mass to be 1.44$\pm$0.14 $M_{\oplus}$. The planet is just outside the Roche limit, with $P_{\rm orb}/P_{\rm Roche}$ = 1.13 $\pm0.10$. The strong tidal force likely deforms the planet into a triaxial ellipsoid with a long axis that is $\sim$10\% longer than the short axis. Assuming a reduced stellar tidal quality factor $Q_\star^\prime \approx10^7$, we predict that tidal orbital decay will cause TOI-6255 to reach the Roche limit in roughly 400 Myr. Such tidal disruptions may produce the possible signatures of planet engulfment that have been on stars with anomalously high refractory elemental abundances compared to its conatal binary companion. TOI-6255 b is also a favorable target for searching for star-planet magnetic interactions, which might cause interior melting and hasten orbital decay. TOI-6255 b is a top target (Emission Spectroscopy Metric of about 24) for phase curve observations with the James Webb Space Telescope., Comment: 18 pages, 7 figures, 5 tables, accepted to AAS Journals. The first RV mass measurement from the Keck Planet Finder

General Relativity describes the trajectories of light-rays through curved spacetime near a massive object. In addition to gravitational lensing, we include an absorbing dielectric medium given by a complex refractive index known as the Drude model. When absorption is included the eikonal becomes complex, with the imaginary part related to the absorption along a ray between emission and observation points. We extend results from the literature to include dispersion in the index of refraction. The complex Hamiltonian splits into a real part that describes the equations of motion and a constraint equation that governs the momentum loss in the system. We work in coordinates which are fully real, with a real metric in physical spacetime. We assume the dust and plasma distributions of the Drude matter to coincide and vary as a power-law $1/r^h$. We find that transmission requires $h>1$, otherwise exponential absorption occurs along ray paths. We use ray-tracing through strongly absorbing matter near the surface of the compact star, as well as specializing to a point-lens in the weak-field limit with weakly absorbing matter to generate potentially observable light curves for distant observers. In the appropriate limits, our theory reproduces results from the literature., Comment: Comments Welcome!

This paper demonstrates the impact of state-of-the-art instrumental calibration techniques on the precision of arrival times obtained from 9.6 years of observations of millisecond pulsars using the Murriyang 64-m CSIRO Parkes Radio Telescope. Our study focuses on 21-cm observations of 25 high-priority pulsars that are regularly observed as part of the Parkes Pulsar Timing Array (PPTA) project, including those predicted to be the most susceptible to calibration errors. We employ Measurement Equation Template Matching (METM) for instrumental calibration and Matrix Template Matching (MTM) for arrival time estimation, resulting in significantly improved timing residuals with up to a sixfold reduction in white noise compared to arrival times estimated using Scalar Template Matching and conventional calibration based on the Ideal Feed Assumption. The median relative reduction in white noise is 33 percent, and the maximum absolute reduction is 4.5 microseconds. For PSR J0437-4715, METM and MTM reduce the best-fit power-law amplitude (2.7 sigma) and spectral index (1.7 sigma) of the red noise in the arrival time residuals, which can can be tentatively interpreted as mitigation of 1/f noise due to otherwise unmodeled steps in polarimetric response. These findings demonstrate the potential to directly enhance the sensitivity of pulsar timing array experiments through more accurate methods of instrumental calibration and arrival time estimation., Comment: 30 pages, 9 figures, accepted for publication in The Astrophysical Journal

Observing and characterizing young planetary systems can aid in unveiling the evolutionary mechanisms that sculpt the mature exoplanet population. As an all-sky survey, NASA's Transiting Exoplanet Survey Satellite (TESS) has expanded the known young planet population as it has observed young comoving stellar populations. This work presents the discovery of a multiplanet system orbiting the 61 Myr old G4V star TIC 434398831 (M = 0.99 Msun, R = 0.91 Rsun, Teff = 5638 K, Tmag = 11.31) located in the Theia 116 comoving population. We estimate the population's age based on rotation periods measured from the TESS light curves, isochrone fitting, and measurements of lithium equivalent widths in the spectra of Theia 116 members. The TESS FFI light curves reveal a mini-Neptune (Rb = 3.51 Rearth, Pb = 3.69 days) and super-Neptune (Rc = 5.63 Rearth, Pc = 6.21 days) with an orbital period ratio slightly larger than 5:3. Follow-up observations from CHEOPS and ground-based telescopes confirm the transits of TIC 434398831 b and c, and constrain their transit times. We explore the potential mass-loss histories of the two planets in order to probe possible initial conditions of the planets immediately after formation., Comment: 14 pages, 13 figures, 5 tables. Submitted to MNRAS