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Thick honeycomb-like electrospun scaffold with nanoparticles of hydroxyapatite (nHA) recently demonstrated its potential to promote proliferation and differentiation of a murine embryonic cell line (C3H10T1/2) to osteoblasts. In order to distinguish the respective effects of the structure and the composition on cell differentiation, beads-on-string fibers were used to manufacture thick honeycomb-like scaffolds without nHA. Mechanical and biological impacts of those beads-on string fibers were evaluated. Uniaxial tensile test showed that beads-on-string fibers decreased the Young Modulus and maximal stress but kept them appropriate for tissue engineering. C3H10T1/2 were seeded and cultured for 6 days on the scaffolds without any growth factors. Viability assays revealed the biocompatibility of the beads-on-string scaffolds, with adequate cells-materials interactions observed by confocal microscopy. Alkaline phosphatase staining was performed at day 6 in order to compare the early differentiation of cells to bone fate. The measure of stained area and intensity confirmed the beneficial effect of both honeycomb structure and nHA, independently. Finally, we showed that honeycomb-like electrospun scaffolds could be relevant candidates for promoting bone fate to cells in the absence of nHA. It offers an easier and faster manufacture process, in particular in bone-interface tissue engineering, permitting to avoid the dispersion of nHA and their interaction with the other cells.

In this paper, we propose a simple method for testing identifying assumptions in parametric separable models, namely treatment exogeneity, instrument validity, and/or homoskedasticity. We show that the testable implications can be written in the intersection bounds framework, which is easy to implement using the inference method proposed in Chernozhukov, Lee, and Rosen (2013), and the Stata package of Chernozhukov et al. (2015). Monte Carlo simulations confirm that our test is consistent and controls size. We use our proposed method to test the validity of some commonly used instrumental variables, such as the average price in other markets in Nevo and Rosen (2012), the Bartik instrument in Card (2009), and the test rejects both instrumental variable models. When the identifying assumptions are rejected, we discuss solutions that allow researchers to identify some causal parameters of interest after relaxing functional form assumptions. We show that the IV model is nontestable if no functional form assumption is made on the outcome equation, when there exists a one-to-one mapping between the continuous treatment variable, the instrument, and the first-stage unobserved heterogeneity.

A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. chemical disorder) of a large random alloy within a small crystal structure. The ability to generate small representations of random alloys, with the restriction to crystal systems, results from using the fixed-lattice cluster correlations to describe structural characteristics. A more general description of the structural characteristics of atomic systems is obtained using complete sets of atomic environment descriptors. These are used within for generating representative atomic structures without restriction to fixed lattices. A general data-driven approach is provided utilizing the atomic cluster expansion(ACE) basis. The N-body ACE descriptors are a complete set of atomic environment descriptors that span both chemical and spatial degrees of freedom and are used within for describing atomic structures. The generalized representative structure(GRS) method presented within generates small atomic structures that reproduce ACE descriptor distributions corresponding to arbitrary structural and chemical complexity. It is shown that systematically improvable representations of crystalline systems on fixed parent lattices, amorphous materials, liquids, and ensembles of atomic structures may be produced efficiently through optimization algorithms. We highlight reduced representations of atomistic machine-learning training datasets that contain similar amounts of information and small 40-72 atom representations of liquid phases. The ability to use GRS methodology as a driver for informed novel structure generation is also demonstrated. The advantages over other data-driven methods and state-of-the-art methods restricted to high-symmetry systems are highlighted.

Autonomous precision navigation to land onto the Moon relies on vision sensors. Computer vision algorithms are designed, trained and tested using synthetic simulations. High quality terrain models have been produced by Moon orbiters developed by several nations, with resolutions ranging from tens or hundreds of meters globally down to few meters locally. The SurRender software is a powerful simulator able to exploit the full potential of these datasets in raytracing. New interfaces include tools to fuse multi-resolution DEMs and procedural texture generation. A global model of the Moon at 20m resolution was integrated representing several terabytes of data which SurRender can render continuously and in real-time. This simulator will be a precious asset for the development of future missions., Comment: 8 pages, 6 figures, Proceedings of the 73rd International Astronautical Congress (IAC), Paris, France, 18-22 November 2022. Contribution reference: IAC-22,A3,IP,44,x71795

Vision Based Navigation consists in utilizing cameras as precision sensors for GNC after extracting information from images. To enable the adoption of machine learning for space applications, one of obstacles is the demonstration that available training datasets are adequate to validate the algorithms. The objective of the study is to generate datasets of images and metadata suitable for training machine learning algorithms. Two use cases were selected and a robust methodology was developed to validate the datasets including the ground truth. The first use case is in-orbit rendezvous with a man-made object: a mockup of satellite ENVISAT. The second use case is a Lunar landing scenario. Datasets were produced from archival datasets (Chang'e 3), from the laboratory at DLR TRON facility and at Airbus Robotic laboratory, from SurRender software high fidelity image simulator using Model Capture and from Generative Adversarial Networks. The use case definition included the selection of algorithms as benchmark: an AI-based pose estimation algorithm and a dense optical flow algorithm were selected. Eventually it is demonstrated that datasets produced with SurRender and selected laboratory facilities are adequate to train machine learning algorithms., Comment: 6 pages, 4 figures, preprint of the proceedings of ESA SPAICE conference 2024

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated., Comment: Prepared for submission to JINST

Many identification results in instrumental variables (IV) models hold without requiring any restrictions on the distribution of potential outcomes, or how those outcomes are correlated with selection behavior. This enables IV models to allow for arbitrary heterogeneity in treatment effects and the possibility of selection on gains in the outcome. I provide a necessary and sufficient condition for treatment effects to be point identified in a manner that does not restrict outcomes when the instruments take a finite number of values. The condition generalizes the well-known LATE monotonicity assumption, and unifies a wide variety of other known IV identification results. The result also yields a brute-force approach to reveal all selection models that allow for point identification of treatment effects without restricting outcomes, and then enumerate all of the identified parameters within each such selection model. The search uncovers new selection models that yield identification, provides impossibility results for others, and offers opportunities to relax assumptions on selection used in existing literature.

The value of school libraries is well-established, with reviews and studies worldwide highlighting the impact on children and young people's academic achievement and literacy outcomes. Yet, it is still not a statutory requirement for schools to have a school library or school library system. As such, there are no official figures as to the number or proportion of schools that have a school library or school librarian in the UK. This report provides an up-to-date picture of school libraries at both primary and secondary schools in the UK. It focuses on what is known about the extent of current school library provision, the evidence of the need for further support of school libraries, and the impact that school libraries can have on children and young people.

The operation of twinning a graph at a vertex was introduced by Foley, Ho\`ang, and Merkel (2019), who conjectured that twinning preserves $e$-positivity of the chromatic symmetric function. A counterexample to this conjecture was given by Li, Li, Wang, and Yang (2021). In this paper, we prove that $e$-positivity is preserved by the twinning operation on cycles, by giving an $e$-positive generating function for the chromatic symmetric function, as well as an $e$-positive recurrence. We derive similar $e$-positive generating functions and recurrences for twins of paths. Our methods make use of the important triple deletion formulas of Orellana and Scott (2014), as well as new symmetric function identities., Comment: 35 pages, 2 tables, 9 figures

Laboratory measurements often use several instruments to fully explore the relevant parameter space; such as, an external lock-in amplifier, an electromagnet, an RF generator, etc.. Ordinarily, these instruments have to be individually controlled and their parameters have to be manually recorded. MacroQueue enables effortless measurements throughout these high-dimensional parameter space systems. MacroQueue is a modular software designed for controlling and automating various laboratory equipment in sync without requiring coding ability. Currently, it includes functions to control the 3 major commercial scanning tunneling microscopes, CreaTec, RHK, and Scienta Omicron in combination with any other instruments that are a part of the systems. It can be extended to control any instrument that can be controlled via Python., Comment: 4 pages; 3 figures

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range $0.1-1$ and $w_a<0$. This preference is 2.6$\sigma$ for the DESI+CMB combination, and persists or grows when SN~Ia are added in, giving results discrepant with the $\Lambda$CDM model at the $2.5\sigma$, $3.5\sigma$ or $3.9\sigma$ levels for the addition of Pantheon+, Union3, or DES-SN5YR datasets respectively. For the flat $\Lambda$CDM model with the sum of neutrino mass $\sum m_\nu$ free, combining the DESI and CMB data yields an upper limit $\sum m_\nu < 0.072$ $(0.113)$ eV at 95% confidence for a $\sum m_\nu>0$ $(\sum m_\nu>0.059)$ eV prior. These neutrino-mass constraints are substantially relaxed in models beyond $\Lambda$CDM. [Abridged.], Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Typos corrected and a new figure and discussion added to Appendix A

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon ($r_d$), we measure the expansion at $z_{\rm eff}=2.33$ with 2\% precision, $H(z_{\rm eff}) = (239.2 \pm 4.8) (147.09~{\rm Mpc} /r_d)$ km/s/Mpc. Similarly, we present a 2.4\% measurement of the transverse comoving distance to the same redshift, $D_M(z_{\rm eff}) = (5.84 \pm 0.14) (r_d/147.09~{\rm Mpc})$ Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters., Comment: This DESI Collaboration Key Publication is part of the 2024 publication series using the first year of observations (see https://data.desi.lbl.gov/doc/papers). Minor changes in v4, version accepted for publication in JCAP

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$\alpha$ (Ly$\alpha$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Ly$\alpha$ forest BAO measurement. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Ly$\alpha$ forest. The synthetic data sets span a redshift range $1.8

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1

In evolutionary robotics, jointly optimising the design and the controller of robots is a challenging task due to the huge complexity of the solution space formed by the possible combinations of body and controller. We focus on the evolution of robots that can be physically created rather than just simulated, in a rich morphological space that includes a voxel-based chassis, wheels, legs and sensors. On the one hand, this space offers a high degree of liberty in the range of robots that can be produced, while on the other hand introduces a complexity rarely dealt with in previous works relating to matching controllers to designs and in evolving closed-loop control. This is usually addressed by augmenting evolution with a learning algorithm to refine controllers. Although several frameworks exist, few have studied the role of the \textit{evolutionary dynamics} of the intertwined `evolution+learning' processes in realising high-performing robots. We conduct an in-depth study of the factors that influence these dynamics, specifically: synchronous vs asynchronous evolution; the mechanism for replacing parents with offspring, and rewarding goal-based fitness vs novelty via selection. Results show that asynchronicity combined with goal-based selection and a `replace worst' strategy results in the highest performance., Comment: 9 pages, 8 figures

Many employers bemoan a lack of communication skills relevant to the workplace in their workforce, particularly with their younger intake. This report shows that providing young people who aren't confident communicators with structured oracy and writing activities as well as real-world opportunities to practise those skills with business professionals can improve their communication skills, build their confidence and inspire them to pursue their goals.

Morpho-evolution (ME) refers to the simultaneous optimisation of a robot's design and controller to maximise performance given a task and environment. Many genetic encodings have been proposed which are capable of representing design and control. Previous research has provided empirical comparisons between encodings in terms of their performance with respect to an objective function and the diversity of designs that are evaluated, however there has been no attempt to explain the observed findings. We address this by applying Local Optima Network (LON) analysis to investigate the structure of the fitness landscapes induced by three different encodings when evolving a robot for a locomotion task, shedding new light on the ease by which different fitness landscapes can be traversed by a search process. This is the first time LON analysis has been applied in the field of ME despite its popularity in combinatorial optimisation domains; the findings will facilitate design of new algorithms or operators that are customised to ME landscapes in the future., Comment: Submitted to GECCO-2024

Growing awareness of the environmental impact of digital technologies has led to several isolated initiatives to promote sustainable practices. However, despite these efforts, the environmental footprint of generative AI, particularly in terms of greenhouse gas emissions and water consumption, remains considerable. This contribution first presents the components of this environmental footprint, highlighting the massive CO2 emissions and water consumption associated with training large language models, thus underlining the need to rethink learning and inference methods. The paper also explores the factors and characteristics of models that have an influence on their environmental footprint and demonstrates the existence of solutions to reduce it, such as using more efficient processors or optimising the energy performance of data centres. The potentially harmful effects of AI on the planet and its ecosystem have made environmental protection one of the founding principles of AI ethics at international and European levels. However, this recognition has not yet translated into concrete measures to address it.To address this issue, our contribution puts forward twelve pragmatic recommendations for public action to promote sustainable generative AI, in particular by building a long-term strategy to achieve carbon neutrality for AI models, encouraging international cooperation to set common standards, supporting scientific research and developing appropriate legal and regulatory frameworks.This paper seeks to inform the members of the Interministerial Committee on Generative AI about the environmental challenges of this technology by providing a brief review of the scientific literature on the subject and proposing concrete recommendations of public policy actions to reconcile technological innovation with the need to protect our environment., Comment: in French language

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-$\alpha$ quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use full survey synthetic data to forecast the BAO scale constraining power with DESI., Comment: 42 pages, 17 figures, 7 tables

This report highlights the enduring importance of our Young Readers Programme by providing children with impactful positive reading experiences as well as opportunities to choose and, crucially, keep books. This is particularly important for children from disadvantaged backgrounds, with over 1 in 4 children who receive free school meals telling us that they received their first book of their own as a result of taking part in the Young Readers Programme. Teachers also feel more empowered to support their pupils' reading for pleasure, and the programme creates sustainable change by promoting a school culture that celebrates reading.

Identifying multiple rival reaction products and transient species formed during ultrafast photochemical reactions and determining their time-evolving relative populations are key steps towards understanding and predicting photochemical outcomes. Yet, most contemporary ultrafast studies struggle with clearly identifying and quantifying competing molecular structures/species amongst the emerging reaction products. Here, we show that mega-electronvolt ultrafast electron diffraction in combination with ab initio molecular dynamics calculations offer a powerful route to determining time-resolved populations of the various isomeric products formed after UV (266 nm) excitation of the five-membered heterocyclic molecule 2(5H)-thiophenone. This strategy provides experimental validation of the predicted high (~50%) yield of an episulfide isomer containing a strained 3-membered ring within ~1 ps of photoexcitation and highlights the rapidity of interconversion between the rival highly vibrationally excited photoproducts in their ground electronic state.

$\rm{PtSe_2}$ is a van der Waals material transitioning from an indirect bandgap semiconductor to a semimetal with increasing thickness. Its absorption threshold has been conjectured to originate from interband indirect transitions. By quantitative comparison between broadband ($0.8 - 3.0\,\rm{eV}$) optical absorption of high-quality exfoliated crystals and DFT ab-initio simulations, we prove instead that the optical absorption arises only from direct transitions. This understanding allows us to shed light on the semiconductor to semimetal transition and to explore the effect of stacking and excitons on the optical absorption.

We present a publicly-available code to generate sets of mock Lyman-$\alpha$ (\lya) forest data that have realistic large-scale correlations including those due to the Baryonic Acoustic Oscillations (BAO). The primary purpose of these mocks is to test the analysis procedures of the Extended Baryon Oscillation Survey (eBOSS) and the Dark Energy Spectroscopy Instrument (DESI) surveys. The transmitted flux fraction, $F(\lambda)$, of background quasars due to \lya\ absorption in the intergalactic medium (IGM) is simulated using the Fluctuating Gunn-Petterson Approximation (FGPA) applied to Gaussian random fields produced through the use of fast Fourier transforms (FFT). The output includes the IGM-\lya\ transmitted flux fraction along quasar lines of sight and a catalog of high-column-density systems appropriately placed at high-density regions of the IGM. This output serves as input to additional code that superimposes the IGM tranmission on realistic quasar spectra, adds absorption by high-column-density systems and metals, and simulates instrumental transmission and noise. Redshift space distortions (RSD) of the flux correlations are implemented by including the large-scale velocity-gradient field in the FGPA resulting in a correlation function of $F(\lambda)$ that can be accurately predicted. One hundred realizations have been produced over the 14,000 deg$^2$ DESI survey footprint with 100 quasars per deg$^{2}$. The analysis of these realizations shows that the correlations of $F(\lambda)$ follows the prediction within the accuracy of eBOSS survey. The most time-consuming part of the mock production occurs before application of the FGPA, and the existing pre-FGPA forests can be used to easily produce new mock sets with modified redshift-dependent bias parameters or observational conditions, Comment: accepted by JCAP

Health-related quality of life (Hr-QoL) scales provide crucial information on neurodegenerative disease progression, help improving patient care, and constitute a meaningful endpoint for therapeutic research. However, Hr-QoL progression is usually poorly documented, as for multiple system atrophy (MSA), a rare and rapidly progressing alpha-synucleinopathy. This work aimed to describe Hr-QoL progression during the natural course of MSA, explore disparities between patients, and identify informative items using a four-step statistical strategy.We leveraged the data of the French MSA cohort comprising annual assessments with the MSA-QoL questionnaire for more than 500 patients over up to 11 years. The four-step strategy (1) determined the subdimensions of Hr-QoL in MSA; (2) modelled the subdimension trajectories over time, accounting for the risk of death; (3) mapped the sequence of item impairments with disease stages; and (4) identified the most informative items specific to each disease stage.Among the 536 patients included, 50% were women and they were aged on average 65.1 years old at entry. Among them, 63.1% died during the follow-up. Four dimensions were identified. In addition to the original motor, nonmotor, and emotional domains, an oropharyngeal component was highlighted. While the motor and oropharyngeal domains deteriorated rapidly, the nonmotor and emotional aspects were already slightly to moderately impaired at cohort entry and deteriorated slowly over the course of the disease. Impairments were associated with sex, diagnosis subtype, and delay since symptom onset. Except for the emotional domain, each dimension was driven by key identified items.Hr-QoL is a multidimensional concept that deteriorates progressively over the course of MSA and brings essential knowledge for improving patient care. As exemplified with MSA, the thorough description of Hr-QoL using the 4-step original analysis can provide new perspectives on neurodegenerative diseases' management to ultimately deliver better support focused on the patient's perspective.

Semiconductor quantum dots are promising candidates for the generation of nonclassical light. Coupling a quantum dot to a device capable of providing polarization-selective enhancement of optical transitions is highly beneficial for advanced functionalities such as efficient resonant driving schemes or applications based on optical cyclicity. Here, we demonstrate broadband polarization-selective enhancement by coupling a quantum dot emitting in the telecom O-band to an elliptical bullseye resonator. We report bright single-photon emission with a degree of linear polarization of 96%, Purcell factor of 3.9, and count rates up to 3 MHz. Furthermore, we present a measurement of two-photon interference without any external polarization filtering and demonstrate compatibility with compact Stirling cryocoolers by operating the device at temperatures up to 40 K. These results represent an important step towards practical integration of optimal quantum dot photon sources in deployment-ready setups.

The UK continues to face a huge adult-literacy challenge, with a sizeable percentage of the UK adult population having very low literacy skills. In addition to highlighting the literacy challenge in the UK, this report shows these individuals experience negative impacts on personal relationships, wellbeing, health, and education, as well as a greater risk of unemployment or being in low-paid work. In addition to many people struggling with low literacy skills, the report also showed that there are also many negative perceptions around, and attitudes towards, literacy. If more action is not taken to tackle low literacy in adults, there is the risk of perpetuating and reinforcing an intergenerational cycle of disadvantage.

A popular approach to deploying scientific applications in high performance computing (HPC) is Linux containers, which package an application and all its dependencies as a single unit. This image is built by interpreting instructions in a machine-readable recipe, which is faster with a build cache that stores instruction results for re-use. The standard approach (used e.g. by Docker and Podman) is a many-layered union filesystem, encoding differences between layers as tar archives. Our experiments show this performs similarly to layered caches on both build time and disk usage, with a considerable advantage for many-instruction recipes. Our approach also has structural advantages: better diff format, lower cache overhead, and better file de-duplication. These results show that a Git-based cache for layer-free container implementations is not only possible but may outperform the layered approach on important dimensions., Comment: 12 pages, 12 figures

Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world, e.g. in robotics applications. Often when evaluating solution over a fixed time period it becomes clear that the objective value will not increase with additional computation time (for example when a two wheeled robot continuously spins on the spot). In such cases, it makes sense to stop the evaluation early to save computation time. However, most approaches to stop the evaluation are problem specific and need to be specifically designed for the task at hand. Therefore, we propose an early stopping method for direct policy search. The proposed method only looks at the objective value at each time step and requires no problem specific knowledge. We test the introduced stopping criterion in five direct policy search environments drawn from games, robotics and classic control domains, and show that it can save up to 75% of the computation time. We also compare it with problem specific stopping criteria and show that it performs comparably, while being more generally applicable.

Machine learning (ML) enables the development of interatomic potentials that promise the accuracy of first principles methods while retaining the low cost and parallel efficiency of empirical potentials. While ML potentials traditionally use atom-centered descriptors as inputs, different models such as linear regression and neural networks can map these descriptors to atomic energies and forces. This begs the question: what is the improvement in accuracy due to model complexity irrespective of choice of descriptors? We curate three datasets to investigate this question in terms of ab initio energy and force errors: (1) solid and liquid silicon, (2) gallium nitride, and (3) the superionic conductor LGPS. We further investigate how these errors affect simulated properties with these models and verify if the improvement in fitting errors corresponds to measurable improvement in property prediction. Since linear and nonlinear regression models have different advantages and disadvantages, the results presented herein help researchers choose models for their particular application. By assessing different models, we observe correlations between fitting quantity (e.g. atomic force) error and simulated property error with respect to ab initio values. Such observations can be repeated by other researchers to determine the level of accuracy, and hence model complexity, needed for their particular systems of interest.

The $q$-Onsager algebra, denoted $O_q$, is defined by two generators $W_0, W_1$ and two relations called the $q$-Dolan-Grady relations. Recently, Terwilliger introduced some elements of $O_q$, said to be alternating. These elements are denoted $\{{W}_{-k}\}_{k=0}^{\infty}, \{{W}_{k+1}\}_{k=0}^{\infty}, \{{G}_{k+1}\}_{k=0}^{\infty}, \{{\tilde{G}}_{k+1}\}_{k=0}^{\infty}$. The alternating elements of $O_q$ are defined recursively. By construction, they are polynomials in $W_0$ and $W_1$. It is currently unknown how to express these polynomials in closed form. In this paper, we consider an algebra $T_q$, called the quantum torus. We present a basis for $T_q$ and define an algebra homomorphism $p: O_q \mapsto T_q$. In our main result, we express the $p$-images of the alternating elements of $O_q$ in the basis for $T_q$. These expressions are in a closed form that we find attractive., Comment: 23 pages. Remark 4.5 added, minor typographical changes made

A shadow molecular dynamics scheme for flexible charge models is presented, where the shadow Born-Oppenheimer potential is derived from a coarse-grained approximation of range-separated density functional theory. The interatomic potential, including the atomic electronegativities and the charge-independent short-range part of the potential and force terms, are modeled by the linear atomic cluster expansion (ACE), which provides a computationally efficient alternative to many machine learning methods. The shadow molecular dynamics scheme is based on extended Lagrangian (XL) Born-Oppenheimer molecular dynamics (BOMD) [Eur. Phys. J. B 94, 164 (2021)]. XL-BOMD provides a stable dynamics, while avoiding the costly computational overhead associated with solving an all-to-all system of equations, which normally is required to determine the relaxed electronic ground state prior to each force evaluation. To demonstrate the proposed shadow molecular dynamics scheme for flexible charge models using the atomic cluster expansion, we emulate the dynamics generated from self-consistent charge density functional tight-binding (SCC-DFTB) theory using a second-order charge equilibration (QEq) model. The charge-independent potentials and electronegativities of the QEq model are trained for a supercell of uranium oxide (UO2) and a molecular system of liquid water. The combined ACE + XL-QEq dynamics are stable over a wide range of temperatures both for the oxide and the molecular systems, and provide a precise sampling of the Born-Oppenheimer potential energy surfaces. Accurate ground Coulomb energies are produced by the ACE-based electronegativity model during an NVE simulation of UO2, predicted to be within 1 meV of those from SCC-DFTB on average during comparable simulations.

Magnetic multilayers are a promising platform for storage and logic devices based on skyrmion spin textures, due to the large materials phase space for tuning properties. Epitaxial superlattice structures of [Pt/Co/Cu]n thin films were grown by molecular beam epitaxy at room temperature. Spin-polarized scanning tunneling microscopy (SP-STM) of these samples was used to probe the connection between surface structure and skyrmion morphology with nanoscale spatial resolution. Irregular-shaped skyrmion bubbles were observed, with effective diameters from 20-200 nm that are much larger than the nanoscale grain structure of the surface topography. Nucleation, annihilation, and motion of skyrmion bubbles could be driven using the stray field of the ferromagnetic tip in repeated imaging, and spin-polarized current/voltage pulses. Our detailed comparison of STM topography and differential conductance images shows that there are no surface defects or inhomogeneities at length scales that could account for the range in skyrmion bubble size or shape observed in the measurements., Comment: 11 pages, 5 figures

Introducing magnetism to the surface state of topological insulators, such as Bi2Te3, can lead to a variety of interesting phenomena. We use scanning tunneling microscopy (STM) to study a single quintuple layer (QL) of the van der Waals magnet Fe3GeTe2 (FGT) that is grown on Bi2Te3 via molecular beam epitaxy. STM topographic images show that the FGT grows as free-standing islands on Bi2Te3 and outwards from Bi2Te3 steps. Atomic resolution imaging shows atomic lattices of 390 +- 10 pm for FGT and 430 +- 10 pm for Bi2Te3, consistent with the respective bulk crystals. A moir\'e pattern is observed on FGT regions with a periodicity of 4.3 +- 0.4 nm that can be attributed solely to this lattice mismatch and thus indicates zero rotational misalignments. While most of the surface is covered by a single QL of the FGT, there are small double QL regions, as well as regions with distinct chemical terminations due to an incomplete QL. The most common partial QL surface termination is the FeGe layer, in which the top two atomic layers are missing. This termination has a distinctive electronic structure and a (sqrt3 x sqrt3)R30 reconstruction overlaid on the moir\'e pattern in STM images. Magnetic circular dichroism (MCD) measurements confirm these thin FGT films are ferromagnetic with TC ~190 K., Comment: 12 pages, 5 figures

Children's literacy development begins long before formal schooling, with parents and the home environment exerting important influences on the development of their children's language skills. A focus on the early years and the home learning environment of children is therefore crucial to ensure that they get the best possible foundation for their literacy skills. There is some research has shown that the pandemic and associated lockdowns have led to an increase in home learning activities (e.g. Davies et al., 2021). However it also has shown that, overall, parents engaged in fewer home learning activities in 2021 compared with the two previous years. There have likely been various reasons for changes in the home learning environment during the pandemic. Indeed, it's not far-fetched to consider the increased isolation and lack of contact and support from others leading to insecurity for parents when it comes to supporting their child in the home. With these pressures, developing a home learning environment may be of less priority to a parent. Alternatively, rather than not being a priority, some parents may have lacked the resources or time to consider alternatives to early learning engagement. Finally, stress and anxiety surrounding the pandemic may have prevented parents from engaging in activity as normal. This report synthesises information from the following sources to provide insight into the importance of the home learning environment and early language skills: (1) Existing literature; (2) Survey data of parents the National Literacy Trust commissioned from One Poll in 2019 (n = 2,000) and 2020 (n = 2,000), and Savanta ComRes in 2021 (n = 1,562); (3) Insight from the 2015 and 2021/2 evaluation of our Early Words Together programme. [This report was commissioned by Paramount as part of a partnership between the National Literacy Trust and Blue's Clues & You!.]

Survey questions often elicit responses on ordered scales for which the definitions of the categories are subjective, possibly varying by individual. This paper clarifies what is learned when these subjective reports are used as an outcome in regression-based causal inference. When a continuous treatment variable is statistically independent of both i) potential outcomes; and ii) heterogeneity in reporting styles, a nonparametric regression of integer category numbers on that variable uncovers a positively-weighted linear combination of causal responses among individuals who are on the margin between adjacent response categories. Though the weights do not integrate to one, the ratio of local regression derivatives with respect to two such explanatory variables identifies the relative magnitudes of convex averages of their effects. When results are extended to discrete treatment variables, different weighting schemes apply to different regressors, making comparisons of magnitude less informative. I obtain a partial identification result for comparing the effects of a discrete treatment variable to those of another treatment variable when there are many categories and individual reporting functions are linear. I also provide results for identification using instrumental variables.

Research has shown that book ownership has a significant impact on life outcomes. In 2019, we found that that children who reported that they had a book of their own were not only more engaged with reading but also six times more likely to read above the level expected for their age than children who did not own a book (22% vs. 3.6%). We included a question on book ownership in our Annual Literacy Survey, which was conducted between January and March 2021. Based on the responses of the 34,435 children and young people who answered this question: (1) Almost 6% of children and young people said they did not have a book of their own at home -- this equates to 413,068 children and young people in the UK; (2) More children who receive free school meals (FSMs) said that they did not have a book of their own at home compared with their peers who do not receive FSMs (9.2% vs. 5.3%); and (3) Book ownership was associated with greater reading enjoyment and frequency. More than twice as many of those who had a book of their own said that they enjoyed reading (52.8% vs. 21.1%), and more than twice as many read daily in their free time (31.8% vs. 13.5%) compared with those who did not have a book of their own.

The number of children and young people in England who speak languages other than English at home has grown in the past decade, increasing from 14.6% in 2011 to 19.3% in 2021. This has understandably sparked an interest in research around reading for multilingual pupils or those with English as an additional language (EAL). Given the apparent lack of insight into the reading engagement of children and young people who speak a language other than English at home, the authors included a few questions in the Annual Literacy Survey, which was conducted in early 2021. This report celebrates multilingual young people's diverse linguistic backgrounds and skills by focusing on their reading enjoyment, behaviours and linguistic identity. This report focuses particularly on 10,000 multilingual young people aged 11 to 16 and explore how much they enjoy reading, how often they read at home and how they feel about reading multilingually. The report also discusses their multilingual language identity and recognition of multilingualism, as well their experiences of bullying due to their linguistic background.

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

We present time-series photometry during eruption of the extremely fast nova V1674 Herculis (Nova Her 2021). The 2021 light curve showed periodic signals at 0.152921(3) d and 501.486(5) s, which we interpret as respectively the orbital and white dwarf spin-periods in the underlying binary. We also detected a sideband signal at the /difference/ frequency between these two clocks. During the first 15 days of outburst, the spin-period appears to have increased by 0.014(1)%. This increase probably arose from the sudden loss of high-angular-momentum gas ("the nova explosion") from the rotating, magnetic white dwarf. Both periodic signals appeared remarkably early in the outburst, which we attribute to the extreme speed with which the nova evolved (and became transparent to radiation from the inner binary). After that very fast initial increase of ~71 ms, the spin-period commenced a steady decrease of ~160 ms/year -- about 100x faster than usually seen in intermediate polars. This is probably due to high accretion torques from very high mass-transfer rates, which might be common when low-mass donor stars are strongly irradiated by a nova outburst., Comment: PDF, 10 pages, 1 table, 3 figures; in preparation; more info at http://cbastro.org/

Semiconductor quantum dots embedded in hybrid circular Bragg gratings are a promising platform for the efficient generation of nonclassical light. The scalable fabrication of multiple devices with similar performance is highly desirable for their practical use as sources of single and entangled photons, while the ability to operate at telecom wavelength is essential for their integration with the existing fiber infrastructure. In this work we combine the promising properties of broadband hybrid circular Bragg gratings with a membrane-transfer process performed on 3" wafer scale. We develop and study single-photon sources based on InAs/GaAs quantum dots emitting in the telecom O-band, demonstrating bright single-photon emission with Purcell factor > 5 and count rates up to 10 MHz. Furthermore, we address the question of reproducibility by benchmarking the performance of 10 devices covering a wide spectral range of 50 nm within the O-band.

This paper studies the identifying power of bunching at kinks when the researcher does not assume a parametric choice model. I find that in a general choice model, identifying the average causal response to the policy switch at a kink amounts to confronting two extrapolation problems, each about the distribution of a counterfactual choice that is observed only in a censored manner. I apply this insight to partially identify the effect of overtime pay regulation on the hours of U.S. workers using administrative payroll data, assuming that each distribution satisfies a weak non-parametric shape constraint in the region where it is not observed. The resulting bounds are informative and indicate a relatively small elasticity of demand for weekly hours, addressing a long-standing question about the causal effects of the overtime mandate.

We report the first detection of large-scale matter flows around cosmic voids at a median redshift z = 2.49. Voids are identified within a tomographic map of the large-scale matter density built from eBOSS Lyman-$\alpha$ (Lya) forests in SDSS Stripe 82. We measure the imprint of flows around voids, known as redshift-space distortions (RSD), with a statistical significance of 10 $\sigma$. The observed quadrupole of the void-forest cross-correlation is described by a linear RSD model. The derived RSD parameter is $\beta = 0.52 \pm 0.05$. Our model accounts for the tomographic effect induced by the Lya data being located along parallel quasar lines of sight. This work paves the way towards growth-rate measurements at redshifts currently inaccessible to galaxy surveys., Comment: 5 pages, 3 figures

To mark World Mental Health Day in 2020, the Bupa Foundation, in partnership with Cheltenham Festivals, the National Literacy Trust and Mind, launched Beyond Words -- a national creative writing project inviting all children, young people and schools to put their feelings about a year like no other into words. Children and young people were invited to write a piece on the theme of 'My 2020' and submit their writing with a chance to get published in a digital anthology in 2021 to celebrate outstanding contributions from children and schools. The project worked with award-winning poets and authors to produce tutorials and resources supporting children, young people and schools with writing and mental wellbeing. As part of the project, the National Literacy Trust was commissioned by Bupa to explore teachers' and young people's perceptions of the project overall and the impact the project might have on young people. To this end, surveys were designed for teachers and young people to complete after submitting their work as part of the project. This report shows that young people and teachers had a positive experience of participating in Beyond Words. Overall, the findings of this report indicate that the project has been successful in supporting the participating young people's wellbeing through writing and reflecting on the year they had.

We present optical photometry of six intermediate polars that exhibit transitions to a low-flux state. For four of these systems, DW Cnc, V515 And, V1223 Sgr and RX J2133.7+5107, we are able to perform timing analysis in and out of the low states. We find that, for DW Cnc and V515 And, the dominant periodicities in the light curves change as the flux decreases, indicating a change in the sources' accretion properties as they transition to the low state. For V1223 Sgr we find that the variability is almost completely quenched at the lowest flux, but do not find evidence for a changing accretion geometry. For RX J2133.7+5107, the temporal properties do not change in the low state, but we do see a period of enhanced accretion that is coincident with increased variability on the beat frequency, which we do not associate with a change in the accretion mechanisms in the system., Comment: 19 pages, 10 figures, accepted for publication in ApJ. The authors recommend downloading the PDF of this paper, as it takes a while to render online

Many robotic tasks require high-dimensional sensors such as cameras and Lidar to navigate complex environments, but developing certifiably safe feedback controllers around these sensors remains a challenging open problem, particularly when learning is involved. Previous works have proved the safety of perception-feedback controllers by separating the perception and control subsystems and making strong assumptions on the abilities of the perception subsystem. In this work, we introduce a novel learning-enabled perception-feedback hybrid controller, where we use Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) to show the safety and liveness of a full-stack perception-feedback controller. We use neural networks to learn a CBF and CLF for the full-stack system directly in the observation space of the robot, without the need to assume a separate perception-based state estimator. Our hybrid controller, called LOCUS (Learning-enabled Observation-feedback Control Using Switching), can safely navigate unknown environments, consistently reach its goal, and generalizes safely to environments outside of the training dataset. We demonstrate LOCUS in experiments both in simulation and in hardware, where it successfully navigates a changing environment using feedback from a Lidar sensor., Comment: Accepted for publication in RA-L

Bookmark Reading supports children's reading in primary schools by offering a six-week programme involving two 30-minute face-to-face sessions each week with a child who needs extra support with their reading. By training volunteers to read with children in their local schools, the programme offers support for children in Years 1 to 3 who are at risk of not meeting the expected standard for reading, and it also helps them to develop a love of reading. The programme is flexible for both schools and volunteers, and sessions are easily scheduled through a digital platform. Bookmark Reading commissioned the National Literacy Trust to explore the impact the programme has on children's reading skills and engagement. To this end, the evaluation was set up to collect information on pupils' reading skill as well as their reading enjoyment, behaviours and confidence before and after taking part in the Bookmark Reading programme. The same information was also collected from classmates who didn't take part in the programme to provide comparative data. The evaluation was also designed to explore volunteers' and teachers' perceptions of the impact on participating pupils, as well as their own experience of the programme. This evaluation sought to collect data from teachers, volunteers and children in the 2019/2020 academic year. Due to the COVID-19 pandemic in the spring of 2020, and the resulting school closures, it became impossible to administer the post-programme surveys and tests with pupils. Therefore, the evaluation was adjusted to focus solely on the perceptions of impact from teachers and volunteers, which were collected through surveys and interviews. This report offers insight into the impact of the programme in the absence of pupil data.

By coupling statewide vacancy/application records with administrative data, we find that activity on the teacher labor market is substantially greater than previously documented, with 53% of novice teachers searching for new positions after their first year and 27% changing schools or leaving the public system. The empirical evidence favors preference alignment theory, showing that first-year teachers are more likely to reenter the labor market after their first year when their preferences and their current employment context diverge. This finding is particularly true for the individuals with a preference for a suburban locale and for school and student characteristics, such as the proportion of students qualifying for free or reduced-price lunch. Once an individual has initiated a job search, preference alignment appears to be unrelated to subsequent mobility. The findings suggest that processes that can facilitate a stronger initial match of novice teachers to their desired employment situations may help mitigate turnover in the following year.

Although numerous studies confirm the importance of school principals, schools often experience high turnover rates and principal shortage. However, we know little about the staffing challenges in rural schools and what promotes applicants to apply for and be hired for principalship. In partnership with the Wisconsin Education Career Access Network, we examine the principal labor dynamics in rural schools using statewide job-openings and application information in Wisconsin. We find that all rural communities--"rural fringe," "rural distant," and "rural remote"--receive equal or high number of applications compared to urban districts. Female candidates are significantly less likely to apply to rural districts, while working in the same district is a considerable advantage to being hired. Among district characteristics, the percentage of students eligible for free or reduced-price lunch tends to reduce the number of applicants in rural schools. Our results highlight the need for policies that are better attuned to the subtle differences in rural contexts.