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Financial large language models (FinLLMs) have been applied to various tasks in business, finance, accounting, and auditing. Complex financial regulations and standards are critical to financial services, which LLMs must comply with. However, FinLLMs’ performance in understanding and interpreting financial regulations has rarely been studied. Therefore, we organize the Regulations Challenge, a shared task at COLING FinNLP-FNP-LLMFinLegal2025. It encourages the academic community to explore the strengths and limitations of popular LLMs. We create 9 novel tasks and corresponding question sets. In this paper, we provide an overview of these tasks and summarize participants’ approaches and results. We aim to raise awareness of FinLLMs’ professional capability in financial regulations. 

Manufacturing continues to be a vital component of the Ohio economy. Ohio’s manufacturing sector employs over 600,000 skilled individuals, the third-largest manufacturing workforce in the U.S. [1]. With additional manufacturing industries moving into Ohio, including Intel and its supply chain partners, there is a growing need for industry-ready, skilled engineering technicians. In addition, with the increasing use of automated systems and network connectivity of these systems in manufacturing operations, technicians need to be equipped with skills in the area of smart manufacturing. This article details the development of a Smart Manufacturing Technology (SMT) associate’s degree that is modeled as an earnand- learn program. The program is equipped with various experiential learning opportunities, and additional industry-recognized certifications are embedded within specific courses. Summer camps were designed and delivered to expose middle and high school students to smart manufacturing and to build a pipeline of students into this program. A professional development summit was delivered each year of the grant. The purpose of the summit was to increase high school instructors’ awareness of smart manufacturing so that they can better advise students about this in-demand field and teach courses in the SMT pathway. 

We introduce a mathematical modeling framework for the conformational dynamics of charged molecules (i.e., solutes) in an aqueous solvent (i.e., water or salted water). The solvent is treated as an incompressible fluid, and its fluctuating motion is described by the Stokes equation with the Landau–Lifschitz stochastic stress. The motion of the solute-solvent interface (i.e., the dielectric boundary) is determined by the fluid velocity together with the balance of the viscous force,hydrostatic pressure, surface tension, solute-solvent van der Waals interaction force, and electrostatic force. The electrostatic interactions are described by the dielectric Poisson–Boltzmann theory.Within such a framework, we derive a generalized Rayleigh–Plesset equation, a nonlinear stochastic ordinary differential equation (SODE), for the radius of a spherical charged molecule, such as anion. The spherical average of the stochastic stress leads to a multiplicative noise. We design and test numerical methods for solving the SODE and use the equation, together with explicit solvent molecular dynamics simulations, to study the effective radius of a single ion. Potentially, our general modeling framework can be used to efficiently determine the solute-solvent interfacial structures and predict the free energies of more complex molecular systems. 

We explore and compare different ways large-scale structure observables in redshift-space and real space can be connected. These include direct computation in La- grangian space, moment expansions and two formulations of the streaming model. We derive for the first time a Fourier space version of the streaming model, which yields an algebraic relation between the real- and redshift-space power spectra which can be compared to ear- lier, phenomenological models. By considering the redshift-space 2-point function in both configuration and Fourier space, we show how to generalize the Gaussian streaming model to higher orders in a systematic and computationally tractable way. We present a closed- form solution to the Zeldovich power spectrum in redshift space and use this as a framework for exploring convergence properties of different expansion approaches. While we use the Zeldovich approximation to illustrate these results, much of the formalism and many of the relations we derive hold beyond perturbation theory, and could be used with ingredients measured from N-body simulations or in other areas requiring decomposition of Cartesian tensors times plane waves. We finish with a discussion of the redshift-space bispectrum, bias and stochasticity and terms in Lagrangian perturbation theory up to 1-loop order. 

Faint star-forming galaxies at z∼2–3 can be used as alternative background sources to probe the Lyα forest in addition to quasars, yielding high sightline densities that enable 3D tomographic reconstruction of the foreground absorption field. Here, we present the first data release from the COSMOS Lyα Mapping And Tomography Observations (CLAMATO) Survey, which was conducted with the LRIS spectrograph on the Keck I telescope. Over an observational footprint of 0.157 deg2 within the COSMOS field, we used 240 galaxies and quasars at 2.17<z<3.00, with a mean comoving transverse separation of 2.37 h-1 Mpc, as background sources probing the foreground Lyα forest absorption at 2.05<z<2.55. The Lyα forest data was then used to create a Wiener- filtered tomographic reconstruction over a comoving volume of 3.15 ́ 105 h-3 Mpc3 with an effective smoothing scale of 2.5 h-1 Mpc. In addition to traditional figures, this map is also presented as a virtual-reality visualization and manipulable interactive figure. We see large overdensities and underdensities that visually agree with the distribution of coeval galaxies from spectroscopic redshift surveys in the same field, including overdensities associated with several recently discovered galaxy protoclusters in the volume. Quantitatively, the map signal-to- noise is S Nwiener » 3.4 over a 3 h−1Mpc top-hat kernel based on the variances estimated from the Wiener filter. This data release includes the redshift catalog, reduced spectra, extracted Lyα forest pixel data, and reconstructed tomographic map of the absorption. These can be downloaded from Zenodo 

This report presents a comprehensive collection of searches for new physics performed by the ATLAS Collaboration during the Run~2 period of data taking at the Large Hadron Collider, from 2015 to 2018, corresponding to about 140~$$^{-1}$$ of $$\sqrt{s}=13$$~TeV proton--proton collision data. These searches cover a variety of beyond-the-standard model topics such as dark matter candidates, new vector bosons, hidden-sector particles, leptoquarks, or vector-like quarks, among others. Searches for supersymmetric particles or extended Higgs sectors are explicitly excluded as these are the subject of separate reports by the Collaboration. For each topic, the most relevant searches are described, focusing on their importance and sensitivity and, when appropriate, highlighting the experimental techniques employed. In addition to the description of each analysis, complementary searches are compared, and the overall sensitivity of the ATLAS experiment to each type of new physics is discussed. Summary plots and statistical combinations of multiple searches are included whenever possible. 

Top-quark pair production is observed in lead–lead ( $\mathrm{Pb}+\mathrm{Pb}$) collisions at $\sqrt{s_{\mathrm{NN}}}=5.02\mathrm{TeV}$at the Large Hadron Collider with the ATLAS detector. The data sample was recorded in 2015 and 2018, amounting to an integrated luminosity of $1.9{\mathrm{nb}}^{-1}$. Events with exactly one electron and one muon and at least two jets are selected. Top-quark pair production is measured with an observed (expected) significance of 5.0 (4.1) standard deviations. The measured top-quark pair production cross section is ${\sigma }_{t\overline{t}}=3.6{}_{-0.9}^{+1.0}\left(\mathrm{stat}\right){}_{-0.5}^{+0.8}\left(\mathrm{syst}\right)\mathrm{\mu }\mathrm{b}$, with a total relative uncertainty of 31%, and is consistent with theoretical predictions using a range of different nuclear parton distribution functions. The observation of this process consolidates the evidence of the existence of all quark flavors in the preequilibrium stage of the quark-gluon plasma at very high energy densities, similar to the conditions present in the early Universe. © 2025 CERN, for the ATLAS Collaboration2025CERN 

A<sc>bstract</sc> A study of the Higgs boson decaying into bottom quarks (H→$$ b\overline{b} $$ $b\overline{b}$) and charm quarks (H→$$ c\overline{c} $$ $c\overline{c}$) is performed, in the associated production channel of the Higgs boson with aWorZboson, using 140 fb⁻¹of proton-proton collision data at$$ \sqrt{s} $$ $\sqrt{s}$= 13 TeV collected by the ATLAS detector. The individual production ofWHandZHwithH→$$ b\overline{b} $$ $b\overline{b}$is established with observed (expected) significances of 5.3 (5.5) and 4.9 (5.6) standard deviations, respectively. Differential cross-section measurements of the gauge boson transverse momentum within the simplified template cross-section framework are performed in a total of 13 kinematical fiducial regions. The search for theH→$$ c\overline{c} $$ $c\overline{c}$decay yields an observed (expected) upper limit at 95% confidence level of 11.5 (10.6) times the Standard Model prediction. The results are also used to set constraints on the charm coupling modifier, resulting in|κ_c| <4.2 at 95% confidence level. Combining theH→$$ b\overline{b} $$ $b\overline{b}$andH→$$ c\overline{c} $$ $c\overline{c}$measurements constrains the absolute value of the ratio of Higgs-charm and Higgs-bottom coupling modifiers (|κ_c/κ_b|) to be less than 3.6 at 95% confidence level. 

The ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess its quality are described, along with the software tools used for data analysis itself. An outlook for the development of these projects towards Run 4 is also provided.