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We report on a direct search for elastic photon-photon scattering using x-ray and $\gamma$ photons from a laser-plasma based experiment. A gamma photon beam produced by a laser wakefield accelerator provided a broadband gamma spectrum extending to above $E_\gamma = 200$ MeV. These were collided with a dense x-ray field produced by the emission from a laser heated germanium foil at $E_x \approx 1.4$ keV, corresponding to an invariant mass of $\sqrt{s} = 1.22 \pm 0.22$ MeV. In these asymmetric collisions elastic scattering removes one x-ray and one high-energy $\gamma$ photon and outputs two lower energy $\gamma$ photons. No changes in the $\gamma$ photon spectrum were observed as a result of the collisions allowing us to place a 95% upper bound on the cross section of $1.5 \times 10^{15}\,\mu$b. Although far from the QED prediction, this represents the lowest upper limit obtained so far for $\sqrt{s} \lesssim 1$ MeV., Comment: 6 pages, 10 figures

The tilt-to-length coupling during the LISA Pathfinder mission has been numerically and analytically modeled for particular timespans. In this work, we investigate the long-term stability of the coupling coefficients of this noise. We show that they drifted slowly (by 1\,$\mu$m/rad and 6$\times10^{-6}$ in 100 days) and strongly correlated to temperature changes within the satellite (8\,$\mu$m/rad/K and 30$\times10^{-6}$/K). Based on analytical TTL coupling models, we attribute the temperature-driven coupling changes to rotations of the test masses and small distortions in the optical setup. Particularly, we show that LISA Pathfinder's optical baseplate was bent during the cooldown experiment, which started in late 2016 and lasted several months.

A precise characterization of the magnetic properties of LISA Pathfinder free falling test-masses is of special interest for future gravitational wave observatory in space. Magnetic forces have an important impact on the instrument sensitivity in the low frequency regime below the millihertz. In this paper we report on the magnetic injection experiments performed throughout LISA Pathfinder operations. We show how these experiments allowed a high precision estimate of the instrument magnetic parameters. The remanent magnetic moment was found to have a modulus of $(0.245\pm0.081)\,\rm{nAm}^2$, the x-component of the background magnetic field within the test masses position was measured to be $(414 \pm 74)$ nT and its gradient had a value of $(-7.4\pm 2.1)\,\mu$T/m. Finally, we also measured the test mass magnetic susceptibility to be $(-3.35\pm0.15)\times$10$^{-5}$ in the low frequency regime. All results are in agreement with on-ground estimates.

LISA Pathfinder was a mission designed to test key technologies required for gravitational wave detection in space. Magnetically driven forces play a key role in the instrument sensitivity in the low-frequency regime, which corresponds to the measurement band of interest for future space-borne gravitational wave observatories. Magnetic-induced forces couple to the test mass motion, introducing a contribution to the relative acceleration noise between the free falling test masses. In this Letter we present the first complete estimate of this term of the instrument performance model. Our results set the magnetic-induced acceleration noise during the February 2017 noise run of $\rm 0.25_{-0.08}^{+0.15}\,fm\,s^{-2}/\sqrt{Hz}$ at 1 mHz and $\rm 1.01_{-0.24}^{+0.73}\, fm\,s^{-2}/\sqrt{Hz}$ at 0.1 mHz. We also discuss how the non-stationarities of the interplanetary magnetic field can affect these values during extreme space weather conditions.

In ornithology, bird species are known to have variedit's widely acknowledged that bird species display diverse dialects in their calls across different regions. Consequently, computational methods to identify bird species onsolely through their calls face critsignificalnt challenges. There is growing interest in understanding the impact of species-specific dialects on the effectiveness of bird species recognition methods. Despite potential mitigation through the expansion of dialect datasets, the absence of publicly available testing data currently impedes robust benchmarking efforts. This paper presents the Dialect Dominated Dataset of Bird Vocalisation, the first cross-corpus dataset that focuses on dialects in bird vocalisations. The DB3V comprises more than 25 hours of audio recordings from 10 bird species distributed across three distinct regions in the contiguous United States (CONUS). In addition to presenting the dataset, we conduct analyses and establish baseline models for cross-corpus bird recognition. The data and code are publicly available online: https://zenodo.org/records/11544734, Comment: accepted by Interspeech 2024

It is often asserted that to control for the effects of confounders, one should include the confounding variables of concern in a statistical model as a covariate. Conversely, it is also asserted that control can only be concluded by design, where the results from an analysis can only be interpreted as evidence of an effect because the design controlled for the cause. To suggest otherwise is said to be a fallacy of cum hoc ergo propter hoc. Obviously, these two assertions create a conundrum: How can the effect of confounder be controlled for with analysis instead of by design without committing cum hoc ergo propter hoc? The present manuscript answers this conundrum., Comment: 30 pages, 6 Figures, r code

The automated generation of imaging reports proves invaluable in alleviating the workload of radiologists. A clinically applicable reports generation algorithm should demonstrate its effectiveness in producing reports that accurately describe radiology findings and attend to patient-specific indications. In this paper, we introduce a novel method, \textbf{S}tructural \textbf{E}ntities extraction and patient indications \textbf{I}ncorporation (SEI) for chest X-ray report generation. Specifically, we employ a structural entities extraction (SEE) approach to eliminate presentation-style vocabulary in reports and improve the quality of factual entity sequences. This reduces the noise in the following cross-modal alignment module by aligning X-ray images with factual entity sequences in reports, thereby enhancing the precision of cross-modal alignment and further aiding the model in gradient-free retrieval of similar historical cases. Subsequently, we propose a cross-modal fusion network to integrate information from X-ray images, similar historical cases, and patient-specific indications. This process allows the text decoder to attend to discriminative features of X-ray images, assimilate historical diagnostic information from similar cases, and understand the examination intention of patients. This, in turn, assists in triggering the text decoder to produce high-quality reports. Experiments conducted on MIMIC-CXR validate the superiority of SEI over state-of-the-art approaches on both natural language generation and clinical efficacy metrics., Comment: The code is available at https://github.com/mk-runner/SEI-Temp or https://github.com/mk-runner/SEI

Background: Drug development is often inefficient, costly and lengthy, yet it is essential for evaluating the safety and efficacy of new interventions. Compared with other disease areas, this is particularly true for Phase II / III cancer clinical trials where high attrition rates and reduced regulatory approvals are being seen. In response to these challenges, seamless clinical trials and master protocols have emerged to streamline the drug development process. Methods: Seamless clinical trials, characterized by their ability to transition seamlessly from one phase to another, can lead to accelerating the development of promising therapies while Master protocols provide a framework for investigating multiple treatment options and patient subgroups within a single trial. Results: We discuss the advantages of these methods through real trial examples and the principals that lead to their success while also acknowledging the associated regulatory considerations and challenges. Conclusion: Seamless designs and Master protocols have the potential to improve confirmatory clinical trials. In the disease area of cancer, this ultimately means that patients can receive life-saving treatments sooner., Comment: 12 manuscript pages, 2 figures and 2 tables

We present an in-depth analysis of the LISA Pathfinder differential acceleration performance over the entire course of its science operations, spanning approximately 500 days. We find that: 1) the evolution of the Brownian noise that dominates the acceleration amplitude spectral density (ASD), for frequencies $f\gtrsim 1\,\text{mHz}$, is consistent with the decaying pressure due to the outgassing of a single gaseous species. 2) between $f=36\,\mu\text{Hz}$ and $1\,\text{mHz}$, the acceleration ASD shows a $1/f$ tail in excess of the Brownian noise of almost constant amplitude, with $\simeq 20\%$ fluctuations over a period of a few days, with no particular time pattern over the course of the mission; 3) at the lowest considered frequency of $f=18\,\mu\text{Hz}$, the ASD significantly deviates from the $1/f$ behavior, because of temperature fluctuations that appear to modulate a quasi-static pressure gradient, sustained by the asymmetries of the outgassing pattern. We also present the results of a projection of the observed acceleration noise on the potential sources for which we had either a direct correlation measurement, or a quantitative estimate from dedicated experiments. These sources account for approximately $40\%$ of the noise power in the $1/f$ tail. Finally, we analyze the possible sources of the remaining unexplained fraction, and identify the possible measures that may be taken to keep those under control in LISA.

AniMAIRE (Anisotropic Model for Atmospheric Ionising Radiation Effects) is a new model and Python toolkit for calculating radiation dose rates experienced by aircraft during anisotropic solar energetic particle events. AniMAIRE expands the physics of the MAIRE+ model such that dose rate calculations can be performed for anisotropic solar energetic particle conditions by supplying a proton or alpha particle rigidity spectrum, a pitch angle distribution, and the conditions of Earth's magnetosphere. In this paper, we describe the algorithm and top-level structure of AniMAIRE and showcase AniMAIRE's capabilities by analysing the dose rate maps that AniMAIRE produces when the time-dependent spectra and pitch angle distribution for GLE71 are inputted. We find that the dose rates AniMAIRE produces for the event fall between the dose rates produced by the WASAVIES and CRAC:DOMO models. Dose rate maps that evolve throughout the event are also shown, and it is found that each peak in the inputted pitch angle distribution generates a dose rate hotspot in each of the polar regions. AniMAIRE has been made available openly online so that it can be downloaded and run freely on local machines and so that the space weather community can easily contribute to it using Github forking., Comment: 22 pages, 7 figures, manuscript submitted to Space Weather Journal. The previous version of this had the incorrect abstract and title, this has been fixed in this version

Light-harvesting devices made from PbS quantum dot (QD) absorbers are one of the many promising technologies of third-generation photovoltaics. Their simple, solution-based fabrication together with a highly tunable and broad light absorption makes their application in newly developed solar cells particularly promising. In order to yield devices with reduced voltage and current losses, PbS QDs need to have strategically passivated surfaces, most commonly achieved through lead iodide and bromide passivation. The interdot spacing is then predominantly filled with residual amorphous lead halide species that remain from the ligand exchange, thus hindering efficient charge transport and reducing device stability. Herein, we demonstrate that a post-treatment by iodide based 2-phenylethlyammonium salts (X-PEAI) and intermediate 2D perovskite formation can be used to manage the lead halide excess in the PbS QD active layer. This treatment results in improved device performance and increased shelf-life stability, demonstrating the importance of interdot spacing management in PbS quantum dot photovoltaics.

The synthesis of metal sulfide nanocrystals is a crucial step in the fabrication of quantum dot (QD) photovoltaics. Control over the quantum dot size during synthesis allows for precise tuning of their optical and electronic properties, making them an appealing choice for electronic applications. This flexibility has led to the implementation of quantum dots in both highly-efficient single junction solar cells and other optoelectronic devices including photodetectors and transistors. Most commonly, metal sulfide quantum dots are synthesized using the hot-injection method utilizing toxic, and air- and moisture sensitive sulfur source: bis(trimethylsilyl) sulfide (TMS)2S. Here, we present bis(stearoyl) sulfide (St2S) as a new type of air-stable sulfur precursor for the synthesis of sulfide-based QDs, which yields uniform, pure, and stable nanocrystals. Photovoltaic devices based on these QDs are equally efficient as those fabricated by (TMS)2S but exhibit an enhanced operational stability. These results highlight that St2S can be widely adopted for the synthesis of metal sulfide quantum dots for a range of optoelectronic applications.

Sigmoid growth models are often used to study population dynamics. The size of a population at equilibrium commonly depends explicitly on the availability of resources, such as an energy or nutrient source, which is not explicit in standard sigmoid growth models. A simple generalised extension of sigmoid growth models is introduced that can explicitly account for this resource-dependence, demonstrated by three examples of this family of models of increasing mathematical complexity. Each model is calibrated and compared to observed data for algae under sea-ice in Antarctic coastal waters. It was found that through careful construction, models satisfying the proposed framework can estimate key properties of a sea-ice break-out controlled tipping point for the algae, which cannot be estimated using standard sigmoid growth models. The proposed broader family of energy-dependent sigmoid growth models likely has usage in many population growth contexts where resources limit population size.

The NeurIPS 2023 Machine Learning for Audio Workshop brings together machine learning (ML) experts from various audio domains. There are several valuable audio-driven ML tasks, from speech emotion recognition to audio event detection, but the community is sparse compared to other ML areas, e.g., computer vision or natural language processing. A major limitation with audio is the available data; with audio being a time-dependent modality, high-quality data collection is time-consuming and costly, making it challenging for academic groups to apply their often state-of-the-art strategies to a larger, more generalizable dataset. In this short white paper, to encourage researchers with limited access to large-datasets, the organizers first outline several open-source datasets that are available to the community, and for the duration of the workshop are making several propriety datasets available. Namely, three vocal datasets, Hume-Prosody, Hume-VocalBurst, an acted emotional speech dataset Modulate-Sonata, and an in-game streamer dataset Modulate-Stream. We outline the current baselines on these datasets but encourage researchers from across audio to utilize them outside of the initial baseline tasks.

This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024. The 6th ABAW Competition addresses contemporary challenges in understanding human emotions and behaviors, crucial for the development of human-centered technologies. In more detail, the Competition focuses on affect related benchmarking tasks and comprises of five sub-challenges: i) Valence-Arousal Estimation (the target is to estimate two continuous affect dimensions, valence and arousal), ii) Expression Recognition (the target is to recognise between the mutually exclusive classes of the 7 basic expressions and 'other'), iii) Action Unit Detection (the target is to detect 12 action units), iv) Compound Expression Recognition (the target is to recognise between the 7 mutually exclusive compound expression classes), and v) Emotional Mimicry Intensity Estimation (the target is to estimate six continuous emotion dimensions). In the paper, we present these Challenges, describe their respective datasets and challenge protocols (we outline the evaluation metrics) and present the baseline systems as well as their obtained performance. More information for the Competition can be found in: https://affective-behavior-analysis-in-the-wild.github.io/6th.

Interactive notebooks are a precious tool for creating graphical user interfaces and teaching materials. Python and Jupyter are becoming increasingly popular in this context, with Jupyter widgets at the core of the interactive functionalities. However, while packages and libraries which offer a broad range of general-purpose widgets exist, there is limited development of specialized widgets for computational physics, chemistry and materials science. This deficiency implies significant time investments for the development of effective Jupyter notebooks for research and education in these domains. Here, we present custom Jupyter widgets that we have developed to target the needs of these communities. These widgets constitute high-quality interactive graphical components and can be employed, for example, to visualize and manipulate data, or to explore different visual representations of concepts, clarifying the relationships existing between them. In addition, we discuss with one example how similar functionality can be exposed in the form of JupyterLab extensions, modifying the JupyterLab interface for an enhanced user experience when working with applications within the targeted scientific domains., Comment: 19 pages, 8 figures

Electrostatic force actuation is a key component of the system of geodesic reference test masses (TM) for the LISA orbiting gravitational wave observatory and in particular for performance at low frequencies, below 1 mHz, where the observatory sensitivity is limited by stray force noise. The system needs to apply forces of order 10$^{-9}$ N while limiting fluctuations in the measurement band to levels approaching 10$^{-15}$ N/Hz$^{1/2}$. We present here the LISA actuation system design, based on audio-frequency voltage carrier signals, and results of its in-flight performance test with the LISA Pathfinder test mission. In LISA, TM force actuation is used to align the otherwise free-falling TM to the spacecraft-mounted optical metrology system, without any forcing along the critical gravitational wave-sensitive interferometry axes. In LISA Pathfinder, on the other hand, the actuation was used also to stabilize the TM along the critical $x$ axis joining the two TM, with the commanded actuation force entering directly into the mission's main differential acceleration science observable. The mission allowed demonstration of the full compatibility of the electrostatic actuation system with the LISA observatory requirements, including dedicated measurement campaigns to amplify, isolate, and quantify the two main force noise contributions from the actuation system, from actuator gain noise and from low frequency ``in band'' voltage fluctuations. These campaigns have shown actuation force noise to be a relevant, but not dominant, noise source in LISA Pathfinder and have allowed performance projections for the conditions expected in the LISA mission.

We investigate spatio-temporal evolution of high-degree acoustic mode frequencies of the Sun and the surface magnetic activity, over the course of multiple solar cycles, to improve our understanding of the connection between the solar interior and atmosphere. We focus on high-degree modes due to their ability to characterize conditions in the shear layer just below the solar surface. Using the full-disk Doppler observations made by the Global Oscillation Network Group (GONG), mode frequencies covering the period from July 2001 to December 2021 are computed through the local helioseismic technique of ring diagrams. Considering 10.7 cm radio flux measurements, the sunspot number, and the local magnetic activity index as solar activity proxies, we note strong correlation between the frequency shifts and each activity index. We further investigate the hemispheric asymmetry in frequency shifts and magnetic activity and find that both the activity and frequencies in the descending phase of cycle 23 were dominant in the southern hemisphere, while in cycle 24 these quantities fluctuated between northern and southern hemispheres. Analyzing the frequency shifts at different latitudes with the progression of solar cycles, we observe that the shifts at mid-latitudes are dominant in the southern hemisphere during the maximum period of solar activity in cycle 24 but the values overlap as the cycle advances towards the minimum activity period. The frequency shifts at the beginning of cycle 25 are found to be dominant in the southern hemisphere following magnetic activity. The analysis presents additional evidence that the variability in oscillation frequencies are caused by both strong and weak magnetic fields., Comment: Accepted for publication in ApJ

Let $S$ be a smooth, quasi-projective complex surface with complex symplectic form $\omega \in H^0(S, K_S)$. This determines a symplectic form $\omega_n$ on the Hilbert scheme of points $S^{[n]}$ for $n \geq 1$. Let $\tau$ be an anti-symplectic involution of $(S,\omega)$: an order two automorphism of $S$ such that $ \tau^*\omega=-\omega$. Then $\tau$ induces an anti-symplectic involution on $(S^{[n]},\omega_n)$ and the fixed point set $(S^{[n]})^\tau$ is a smooth Lagrangian subvariety of $S^{[n]}$. In this paper, we calculate the mixed Hodge structure of $H^*( (S^{[n]})^\tau; \mathbb{Q})$ in terms of the mixed Hodge structures of $H^*( S^\tau;\mathbb{Q})$ and of $H^*( S / \tau; \mathbb{Q})$. We also classify the connected components of $(S^{[n]})^\tau$ and determine their mixed Hodge structures. Our results apply more generally whenever $S$ is a smooth quasi-projective surface, and $\tau$ is an involution of $S$ for which $S^\tau$ is a curve., Comment: 15 pages. Made some minor changes to the discussion of K3 surfaces and added a corollary

In this position paper, we argue that when hypergraphs are used to capture multi-way local relations of data, their resulting topological features describe global behaviour. Consequently, these features capture complex correlations that can then serve as high fidelity inputs to autoencoder-driven anomaly detection pipelines. We propose two such potential pipelines for cybersecurity data, one that uses an autoencoder directly to determine network intrusions, and one that de-noises input data for a persistent homology system, PHANTOM. We provide heuristic justification for the use of the methods described therein for an intrusion detection pipeline for cyber data. We conclude by showing a small example over synthetic cyber attack data.

We obtain bounds on the average size of Bohr sets with coefficients parametrised by polynomials over finite fields and obtain a series of general results and also some sharper results for specific sets which are important for applications to computer science. In particular, we use our estimates to show that a heuristic assumption used in the many variable version of Coppersmith's method holds with high probability. We demonstrate the use of our results on the approximate greatest common divisor problem and obtain a fully rigorous version of the heuristic algorithm of H. Cohn and N. Heninger (2013).

In this paper we analyze the extent to which a mandated kindergarten assessment predicts 3rd grade outcomes, and the academic progression for students from 3rd grade to high school. We find that the kindergarten assessment strongly predicts 3rd grade outcomes, with the math skills assessment being especially predictive of 3rd grade academic outcomes. The kindergarten assessments also illustrate the degree to which there are large inequities in skills when students are assessed in kindergarten. Students from historically disadvantaged groups enter kindergarten with significantly fewer readiness standards met. Our analysis of student academic progression from 3rd grade through high school echoes the kindergarten to 3rd grade results. The 3rd grade test assessment is strongly predictive of all high school outcomes, and we see that those students eligible for free- or reduced-price lunches and students of underrepresented racial or ethnic groups are less likely to have upward academic mobility. In sum, we observed limited academic mobility; students who start out behind generally stay behind.