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Inference for locally stationary processes is often based on some local Whittle-type approximation of the likelihood function defined in the frequency domain. The main reasons for using such a likelihood approximation is that i) it has substantially lower computational cost and better scalability to long time series compared to the time domain likelihood, particularly when used for Bayesian inference via Markov Chain Monte Carlo (MCMC), ii) convenience when the model itself is specified in the frequency domain, and iii) it provides access to bootstrap and subsampling MCMC which exploits the asymptotic independence of Fourier transformed data. Most of the existing literature compares the asymptotic performance of the maximum likelihood estimator (MLE) from such frequency domain likelihood approximation with the exact time domain MLE. Our article uses three simulation studies to assess the finite-sample accuracy of several frequency domain likelihood functions when used to approximate the posterior distribution in time-varying parameter models. The methods are illustrated on an application to egg price data.

Given a finite family of compact subsets of the complex plane we propose a certificate of mutual non-overlapping with respect to area measure. The criterion is stated as a couple of positivity conditions imposed on a four argument analytic/anti-analytic kernel defined in a neighborhood of infinity. In case the compact sets are closures of quadrature domains the respective kernel is rational, enabling an effective matrix analysis algorithm for the non-overlapping decision. The simplest situation of two disks is presented in detail from a matrix model perspective as well as from a Riemann surface potential theoretic interpretation.

We summarise three applications of the obstacle problem to membrane contact, elastoplastic torsion and cavitation modelling, and show how the resulting models can be solved using mixed finite elements. It is challenging to construct fixed computational meshes for any inequality-constrained problem because the coincidence set has an unknown shape. Consequently, we demonstrate how $h$-adaptivity can be used to resolve the unknown coincidence set. We demonstrate some practical challenges that must be overcome in the application of the adaptive method.

The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusing on six key areas: time-sensitive workflows, AI-HPC convergence, multi-facility workflows, heterogeneous HPC environments, user experience, and FAIR computational workflows. The integration of AI and exascale computing has revolutionized scientific workflows, enabling higher-fidelity models and complex, time-sensitive processes, while introducing challenges in managing heterogeneous environments and multi-facility data dependencies. The rise of large language models is driving computational demands to zettaflop scales, necessitating modular, adaptable systems and cloud-service models to optimize resource utilization and ensure reproducibility. Multi-facility workflows present challenges in data movement, curation, and overcoming institutional silos, while diverse hardware architectures require integrating workflow considerations into early system design and developing standardized resource management tools. The summit emphasized improving user experience in workflow systems and ensuring FAIR workflows to enhance collaboration and accelerate scientific discovery. Key recommendations include developing standardized metrics for time-sensitive workflows, creating frameworks for cloud-HPC integration, implementing distributed-by-design workflow modeling, establishing multi-facility authentication protocols, and accelerating AI integration in HPC workflow management. The summit also called for comprehensive workflow benchmarks, workflow-specific UX principles, and a FAIR workflow maturity model, highlighting the need for continued collaboration in addressing the complex challenges posed by the convergence of AI, HPC, and multi-facility research environments.

A concentration index, a standardized covariance between a health variable and relative income ranks, is often used to quantify income-related health inequalities. There is a lack of formal approach to study the effect of an exposure, e.g., education, on such measures of inequality. In this paper we contribute by filling this gap and developing the necessary theory and method. Thus, we define a counterfactual concentration index for different levels of an exposure. We give conditions for their identification, and then deduce their efficient influence function. This allows us to propose estimators, which are regular asymptotic linear under certain conditions. In particular, these estimators are $\sqrt n$-consistent and asymptotically normal, as well as locally efficient. The implementation of the estimators is based on the fit of several nuisance functions. The estimators proposed have rate robustness properties allowing for convergence rates slower than $\sqrt{n}$-rate for some of the nuisance function fits. The relevance of the asymptotic results for finite samples is studied with simulation experiments. We also present a case study of the effect of education on income-related health inequalities for a Swedish cohort.

Foundation models have recently become a popular research direction within computational pathology. They are intended to be general-purpose feature extractors, promising to achieve good performance on a range of downstream tasks. Real-world pathology image data does however exhibit considerable variability. Foundation models should be robust to these variations and other distribution shifts which might be encountered in practice. We evaluate two computational pathology foundation models: UNI (trained on more than 100,000 whole-slide images) and CONCH (trained on more than 1.1 million image-caption pairs), by utilizing them as feature extractors within prostate cancer grading models. We find that while UNI and CONCH perform well relative to baselines, the absolute performance can still be far from satisfactory in certain settings. The fact that foundation models have been trained on large and varied datasets does not guarantee that downstream models always will be robust to common distribution shifts., Comment: Preprint, work in progress

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 700 workflows registered., Comment: 30 pages, 4 figures

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity, reproducibility, and democratized access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative's FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present our recommendations with commentary that reflects our discussions and justifies our choices and adaptations. Like the software and data principles on which they are based, these are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guide rails for adoption and fodder for discussion. Workflows are becoming more prevalent as documented, automated instruments for data analysis, data collection, AI-based predictions, and simulations. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community., Comment: 17 pages, 1 figure, 1 table

Prediction of mRNA gene-expression profiles directly from routine whole-slide images (WSIs) using deep learning models could potentially offer cost-effective and widely accessible molecular phenotyping. While such WSI-based gene-expression prediction models have recently emerged within computational pathology, the high-dimensional nature of the corresponding regression problem offers numerous design choices which remain to be analyzed in detail. This study provides recommendations on how deep regression models should be trained for WSI-based gene-expression prediction. For example, we conclude that training a single model to simultaneously regress all 20530 genes is a computationally efficient yet very strong baseline.

Diffusion models have achieved remarkable progress in generative modelling, particularly in enhancing image quality to conform to human preferences. Recently, these models have also been applied to low-level computer vision for photo-realistic image restoration (IR) in tasks such as image denoising, deblurring, dehazing, etc. In this review paper, we introduce key constructions in diffusion models and survey contemporary techniques that make use of diffusion models in solving general IR tasks. Furthermore, we point out the main challenges and limitations of existing diffusion-based IR frameworks and provide potential directions for future work., Comment: Review paper; any comments and suggestions are most welcome!

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest Gamma-Ray Burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded by 1 s the low-energy (< 10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a Bad Time Interval (BTI) of 64 seconds caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 seconds suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event., Comment: 60 pages, 38 figures, 9 tables

Modern physics experiments are frequently very complex, relying on multiple simultaneous events to happen in order to obtain the desired result. The experiment control system plays a central role in orchestrating the measurement setup: However, its development is often treated as secondary with respect to the hardware, its importance becoming evident only during the operational phase. Therefore, the AEgIS (Antimatter Experiment: Gravity, Interferometry, Spectroscopy) collaboration has created a framework for easily coding control systems, specifically targeting atomic, quantum, and antimatter experiments. This framework, called Total Automation of LabVIEW Operations for Science (TALOS), unifies all the machines of the experiment in a single entity, thus enabling complex high-level decisions to be taken, and it is constituted by separate modules, called MicroServices, that run concurrently and asynchronously. This enhances the stability and reproducibility of the system while allowing for continuous integration and testing while the control system is running. The system demonstrated high stability and reproducibility, running completely unsupervised during the night and weekends of the data-taking campaigns. The results demonstrate the suitability of TALOS to manage an entire physics experiment in full autonomy: being open-source, experiments other than the AEgIS experiment can benefit from it.

The ionization potential (IP) of radium monofluoride (RaF) was measured to be 4.969(2)[10] eV, revealing a relativistic enhancement in the series of alkaline earth monofluorides. The results are in agreement with a relativistic coupled-cluster prediction of 4.969[7] eV, incorporating up to quantum electrodynamics corrections. Using the same computational methodology, an improved calculation for the dissociation energy ($D_{0}$) of 5.54[5] eV is presented. This confirms that radium monofluoride joins the small group of diatomic molecules for which $D_{0}>\mathrm{IP}$, paving the way for precision control and interrogation of its Rydberg states.

The number of degrees-of-freedom (NDoF) in a communication system is limited by the number of antenna ports, element shapes, positions, and the propagation environment. As the number of antenna elements increases within a given region, the NDoF eventually saturates due to correlation of the radiated fields. The maximal NDoF can be determined numerically for communication between two regions using singular value decomposition of a channel model representing wave propagation between densely sampled sources at the transmitter and fields at the receiver. This paper provides a straightforward analytical estimate of the NDoF for arbitrarily shaped transmitter and receiver regions. The analysis show that the NDoF for electrically large regions is approximated by the mutual shadow area of the regions, measured in wavelengths. Several setups illustrate the results, which are then compared with numerical evaluations of the singular values of the propagation channel. These new analytical expressions also simplify to previously established results based on Weyl's law and the paraxial approximation.

Faraday rotation contains information about the magnetic field structure along the line of sight and is an important instrument in the study of cosmic magnetism. Traditional Faraday spectrum deconvolution methods such as RMCLEAN face challenges in resolving complex Faraday dispersion functions and handling large datasets. We develop a deep learning deconvolution model to enhance the accuracy and efficiency of extracting Faraday rotation measures from radio astronomical data, specifically targeting data from the MeerKAT Galaxy Cluster Legacy Survey (MGCLS). We use semi-supervised learning, where the model simultaneously recreates the data and minimizes the difference between the output and the true signal of synthetic data. Performance comparisons with RMCLEAN were conducted on simulated as well as real data for the galaxy cluster Abell 3376. Our semi-supervised model is able to recover the Faraday dispersion with great accuracy, particularly for complex or high-RM signals, maintaining sensitivity across a broad RM range. The computational efficiency of this method is significantly improved over traditional methods. Applied to observations of Abell 3376, we find detailed magnetic field structures in the radio relics, and several AGN. We also apply our model to MeerKAT data of Abell 85, Abell 168, Abell 194, Abell 3186 and Abell 3667., Comment: 20 pages, 20 figures, submitted to Astronomy & Astrophysics

We study the effect of random perturbations in the Human and Nature Dynamics (HANDY) model. HANDY models the interactions between human population, depletion, and consumption of natural resources. HANDY explains how endogenous human--nature interactions could lead to sustainability or collapse in past societies. We introduce a Gaussian random noise perturbation on the population change to represent generic external perturbations. The robustness of the results is investigated with statistical analysis based on probability distributions of specific events. Our study shows that the results of the unperturbed HANDY model are robust under small perturbations of $\lesssim$ 10\% of the Human population. Our results confirm that endogenous dynamics drive the societal cycles. However, exogenous perturbations, such as floods, droughts, earthquakes, volcanic eruptions, infectious disease, epidemics, and wars, can accelerate or delay a collapse cycle., Comment: 26 pages 12 figures

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

This letter proposes a new method for joint state and parameter estimation in uncertain dynamical systems. We exploit the partial errors-in-variables (PEIV) principle and formulate a regression problem in the sense of weighted total least squares, where the uncertainty in the parameter prior is explicitly considered. Based thereon, the PEIV regression can be solved iteratively through the Kalman smoothing and the regularized least squares for estimating the state and the parameter, respectively. The simulations demonstrate improved accuracy of the proposed method compared to existing approaches, including the joint maximum a posterior-maximum likelihood, the expectation maximisation, and the augmented state extended Kalman smoother., Comment: 5 pages

In this work, approximate eight-bit floating-point operations performed using simple integer operations is discussed. For two-bit mantissa formats, faithful rounding can always be obtained for the considered operations. For all operations, correctly rounded results can be obtained for different rounding modes, either directly or by adding a conditional carry in. For three-bit mantissa formats, faithful rounding can be sometimes be obtained directly, while for other operations a conditional carry in must be added. Correctly rounded results can be obtained for most operations and rounding modes using slightly more complicated expressions for the carry in. Hardware implementation results for multiplication using both standard cell and FPGA technology are presented illustrating the potential benefit of integer computation. Especially for FPGA, significant resource savings are obtained., Comment: Submitted to IEEE Symposium on Computer Arithmetic on Feb. 12 2024

The primary goal of the AEgIS experiment is to precisely measure the free fall of antihydrogen within Earth's gravitational field. To this end, a cold ~50K antihydrogen beam has to pass through two grids forming a moir\'e deflectometer before annihilating onto a position-sensitive detector, which shall determine the vertical position of the annihilation vertex relative to the grids with micrometric accuracy. Here we introduce a vertexing detector based on a modified mobile camera sensor and experimentally demonstrate that it can measure the position of antiproton annihilations with an accuracy of $0.62^{+0.40}_{-0.22}\mu m$, which represents a 35-fold improvement over the previous state-of-the-art for real-time antiproton vertexing. Importantly, these antiproton detection methods are directly applicable to antihydrogen. Moreover, the sensitivity to light of the sensor enables the in-situ calibration of the moir\'e deflectometer, significantly reducing systematic errors. This sensor emerges as a breakthrough technology for achieving the \aegis scientific goals and has been selected as the basis for the development of a large-area detector for conducting antihydrogen gravity measurements., Comment: 21 pages, 4 figures, 2 tables

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

The paper reviews some parts of classical potential theory with applications to two dimensional fluid dynamics, in particular vortex motion. Energy and forces within a system of point vortices are similar to those for point charges when the vortices are kept fixed, but the dynamics is different in the case of free vortices. Starting from Bernoulli's equation we derive these laws. Letting the number of vortices tend to infinity leads in the limit to considerations of capacity, harmonic measure and many other notions in potential theory. In particular various kinds of Green functions have a central role in the paper, where we make a difference between electrostatic and hydrodynamic Green function. We also consider the corresponding concepts in the case of closed Riemann surfaces provided with a metric. From a canonically defined monopole Green function we rederive much of the classical theory of harmonic and analytic forms. In the final section of the paper we return to the planar case, then reappearing in form of a symmetric Riemann surface, the Schottky double. Bergman kernels, electrostatic and hydrodynamic, come up naturally, and associated to the Green function the is a certain Robin function which is important for vortex motion and which also relates to capacity functions in classical potential theory., Comment: 104 pages, 6 figures

This paper presents an optimal synthesis of material distributions in obstacles for maximal extinction, scattering, or absorption. The material synthesis is based on an explicit construction utilizing the current distribution derived from physical bounds excited from the far-field. The bounds are expressed in radiation modes for materials restricted by their resistivity and characteristic modes for materials restricted by the contrast. The results are valid for arbitrary shapes, and analytical expressions are provided for spherical shapes.

Aims. We aim to resolve the spatial and kinematic sub-structures in five detached-shell sources to provide detailed constraints for hydrodynamic models that describe the formation and evolution of the shells. Methods. We use observations of the 12 CO (1-0) emission towards five carbon-AGB stars with ALMA. The data have angular resolutions of 0.3 arcsec to 1arcsec and a velocity resolution of 0.3 km/s . This enables us to quantify spatial and kinematic structures in the shells. Results. The observed emission is separated into two distinct components: a more coherent, bright outer shell and a more filamentary, fainter inner shell. The kinematic information shows that the inner sub-shells move at a higher velocity relative to the outer sub-shells. The observed sub-structures confirm the predictions from hydrodynamical models. However, the models do not predict a double-shell structure, and the CO emission likely only traces the inner and outer edges of the shell, implying a lack of CO in the middle layers of the detached shell. Previous estimates of the masses and temperatures are consistent with originating mainly from the brighter subshell, but the total shell masses are likely lower limits. Conclusions. The observed spatial and kinematical splittings of the shells appear consistent with results from hydrodynamical models, provided the CO emission does not trace the H2 density distribution in the shell but rather traces the edges of the shells. It is therefore not possible to constrain the total shell mass based on the CO observations alone. Complementary observations of, e.g., CI as a dissociation product of CO would be necessary to understand the distribution of CO compared to H2., Comment: 18 pages (incl. 5 pages Appendix), 13 Figures

Though diffusion models have been successfully applied to various image restoration (IR) tasks, their performance is sensitive to the choice of training datasets. Typically, diffusion models trained in specific datasets fail to recover images that have out-of-distribution degradations. To address this problem, this work leverages a capable vision-language model and a synthetic degradation pipeline to learn image restoration in the wild (wild IR). More specifically, all low-quality images are simulated with a synthetic degradation pipeline that contains multiple common degradations such as blur, resize, noise, and JPEG compression. Then we introduce robust training for a degradation-aware CLIP model to extract enriched image content features to assist high-quality image restoration. Our base diffusion model is the image restoration SDE (IR-SDE). Built upon it, we further present a posterior sampling strategy for fast noise-free image generation. We evaluate our model on both synthetic and real-world degradation datasets. Moreover, experiments on the unified image restoration task illustrate that the proposed posterior sampling improves image generation quality for various degradations., Comment: CVPRW 2024; Code: https://github.com/Algolzw/daclip-uir

Electromagnetic degrees of freedom are instrumental in antenna design, wireless communications, imaging, and scattering. Larger number of degrees of freedom enhances control in antenna design, influencing radiation patterns and directivity, while in communication systems, it links to spatial channels for increased data rates and reliability, and resolution in imaging. The correlation between computed degrees of freedom and physical quantities is not fully understood, prompting a comparison between classical estimates, Weyl's law, modal expansions, and optimization techniques. In this paper, it is shown that the number of degrees of freedom for arbitrary shaped radiating structures approaches the shadow area measured in squared wavelengths asymptotically as the wavelength decreases.

We present a method for the distributed finite element solution of elliptic boundary value problems using model order reduction on each subdomain of the domain decomposition. We show that the error of the reduction can be succesfully controlled in the $H^1$ norm due to the properly weighted $l^2$ low-rank approximation. Our numerical results demonstrate the technique using tetrahedral meshes with up to 85 million degrees-of-freedom on a laptop computer by distributing the bulk of the model order reduction to the cloud.

To address the learning crisis and other challenges facing children and youth (those 15-24 years of age) it is critical for governments, multilateral and bilateral funders, other donors, and implementers to have a clear understanding of program costs and cost breakdowns to inform financing decisions. For nearly a decade, the Center for Universal Education (CUE) at the Brookings Institution has led the Childhood Cost Data initiative, a research project focused on the collection, analysis, and use of cost data to increase the volume and quality of funding for programs targeting children and youth. The initiative's end goal is to improve learning and life outcomes for the youngest generation through these advancements. As part of this initiative, Brookings developed the Childhood Cost Calculator (C3), intended to facilitate cost analysis. This study introduces C3, the tool's various dimensions and functionalities, and presents learnings from three case studies from piloting the calculator in the education or early childhood development (ECD) sectors in Cambodia, Ghana, and Honduras. It concludes with suggestions for a way forward that supports funders, implementers, and researchers to better use cost data to make strides in tackling the multiple crises facing children and youth today.

We present the Citizen Science program Active Asteroids and describe discoveries stemming from our ongoing project. Our NASA Partner program is hosted on the Zooniverse online platform and launched on 2021 August 31, with the goal of engaging the community in the search for active asteroids -- asteroids with comet-like tails or comae. We also set out to identify other unusual active solar system objects, such as active Centaurs, active quasi-Hilda asteroids, and Jupiter-family comets (JFCs). Active objects are rare in large part because they are difficult to identify, so we ask volunteers to assist us in searching for active bodies in our collection of millions of images of known minor planets. We produced these cutout images with our project pipeline that makes use of publicly available Dark Energy Camera (DECam) data. Since the project launch, roughly 8,300 volunteers have scrutinized some 430,000 images to great effect, which we describe in this work. In total we have identified previously unknown activity on 15 asteroids, plus one Centaur, that were thought to be asteroidal (i.e., inactive). Of the asteroids, we classify four as active quasi-Hilda asteroids, seven as JFCs, and four as active asteroids, consisting of one Main-belt comet (MBC) and three MBC candidates. We also include our findings concerning known active objects that our program facilitated, an unanticipated avenue of scientific discovery. These include discovering activity occurring during an orbital epoch for which objects were not known to be active, and the reclassification of objects based on our dynamical analyses., Comment: 35 pages, 5 figures, 3 tables

We present an analysis of the recent near threshold BESIII data for the nucleon time-like effective form factors. The damped oscillation emerging from the subtraction of the dipole formula is treated in non-perturbative-QCD, making use of the light cone distribution amplitudes expansion. Non-perturbative effects are accounted for by considering Q2-dependent coefficients in such expansions, whose free parameters are determined by fitting to the proton and neutron data. Possible implications and future analysis have been discussed., Comment: 8 pages, 4 figures

This paper presents radiation efficiency and gain bounds for microstrip patch antennas. The presented bounds are shown to be good predictors of antenna performance. Using the bounds, patch miniaturization techniques based on high permittivity substrates and geometrical shaping are compared. Further, a semi-analytic model is developed to approximate the bounds. Measurements are used to validate the bounds. Finally, maximum bandwidth of a microstrip patch antenna is linked to its maximum radiation efficiency.

The problem of substructure characteristic modes is reformulated using a scattering matrix-based formulation, generalizing subregion characteristic mode decomposition to arbitrary computational tools. It is shown that the scattering formulation is identical to the classical formulation based on the background Green's function for lossless systems. The scattering formulation, however, opens a variety of new subregion scenarios unavailable within previous formulations, including cases with lumped or wave ports or subregions in circuits. Thanks to its scattering nature, the formulation is solver-agnostic with the possibility to utilize an arbitrary full-wave method., Comment: 13 pages, 11 figures

A powerful and robust control system is a crucial, often neglected, pillar of any modern, complex physics experiment that requires the management of a multitude of different devices and their precise time synchronisation. The AEgIS collaboration presents CIRCUS, a novel, autonomous control system optimised for time-critical experiments such as those at CERN's Antiproton Decelerator and, more broadly, in atomic and quantum physics research. Its setup is based on Sinara/ARTIQ and TALOS, integrating the ALPACA analysis pipeline, the last two developed entirely in AEgIS. It is suitable for strict synchronicity requirements and repeatable, automated operation of experiments, culminating in autonomous parameter optimisation via feedback from real-time data analysis. CIRCUS has been successfully deployed and tested in AEgIS; being experiment-agnostic and released open-source, other experiments can leverage its capabilities.

We examine the possible existence of quadrupole resonances in exotic atoms containing odd-$A$ nuclei. We find that the spin-flip of the de-exciting exotic particle can induce a resonance, altering the orbital angular momentum of the nucleus by one quanta. This process results in an excited nucleus with a suppression in x-ray photon emissions during the exotic atom cascade. We provide specific cases of antiprotonic atoms of stable elements where this resonance effect is expected to occur. The study of this phenomena may provide insight into the strong interaction of deeply bound antiprotonic states in the proximity of the unpaired nucleon, and serve as a tool for probing short-lived excited nuclear states.