Gravitational form factors (GFFs), defined through the matrix elements of the energy-momentum tensor, provide critical insights into the internal structure of nucleons and nuclei. In particular, their Fourier transforms -- evaluated in the Breit frame -- reveal spatial distributions of mass, pressure, and shear force densities associated with both quark and gluon constituents. This work presents recent measurements of near-threshold $J/\psi$ photoproduction on the proton, performed in Hall C at Jefferson Lab, utilizing data from the electronic decay channels of the $J/\psi$. These results enable the extraction of gluonic gravitational form factors (gGFFs), offering a novel probe of the gluon dynamics within the nucleon. The analysis employs a holographic QCD framework to interpret the threshold behavior of the cross sections and to facilitate the extraction of the gGFFs. The implications of these measurements are discussed in the context of upcoming experimental programs, including the near-threshold electro- and photoproduction studies with SoLID at Jefferson Lab and the $\Upsilon$ production program at the Electron-Ion Collider using the ePIC detector. These future efforts are expected to significantly improve the precision of gGFF determinations and provide essential tests of their universality across different kinematic regimes.

The STAR Collaboration reports measurements of acoplanarity using semi-inclusive distributions of charged-particle jets recoiling from direct photon and $\pi^{0}$ triggers, in central Au-Au and pp collisions at $\sqrt{s_{\rm NN}}=200$ GeV. Significant medium-induced acoplanarity broadening is observed for large but not small recoil jet resolution parameter, corresponding to recoil jet yield enhancement up to a factor of $\approx20$ for trigger-recoil azimuthal separation far from $\pi$. This phenomenology is indicative of the response of the Quark-Gluon Plasma to excitation, but not the scattering of jets off of its quasiparticles. The measurements are not well-described by current theoretical models which incorporate jet quenching.

Artificial intelligence (AI) is transforming not only our daily experiences but also the technological development landscape and scientific research. In this study, we pioneered the application of AI in double-strangeness hypernuclear studies. These studies which investigate quantum systems with strangeness via hyperon interactions provide insights into fundamental baryon-baryon interactions and contribute to our understanding of the nuclear force and composition of neutron star cores. Specifically, we report the observation of a double hypernucleus in nuclear emulsion achieved via innovative integration of machine learning techniques. The proposed methodology leverages generative AI and Monte Carlo simulations to produce training datasets combined with object detection AI for effective event identification. Based on the kinematic analysis and charge identification, the observed event was uniquely identified as the production and decay of resulting from {\Xi}- capture by 14N in the nuclear emulsion. Assuming capture in the atomic 3D state, the binding energy of the two {\Lambda} hyperons in 13B{\Lambda}{\Lambda}, B{\Lambda}{\Lambda}, was determined as 25.57 +- 1.18(stat.) +- 0.07(syst.) MeV. The {\Lambda}{\Lambda} interaction energy obtained was 2.83 +- 1.18(stat.) +- 0.14(syst.) MeV. This study marks a new era in double-strangeness research.

The shapes of the beta spectra of 92Rb and 142Cs, two of the beta decays most relevant for the prediction of the antineutrino spectrum in reactors, have been measured. A new setup composed of two dE-E telescopes has been used. High purity radioactive beams of the isotopes of interest were provided by the IGISOL facility using the JYFLTRAP double Penning trap. The resulting beta spectra have been compared with model predictions using beta decay feedings from total absorption gamma spectroscopy measurements and shape corrections employed in the calculation of the antineutrino spectrum, validating both further. The procedure can be extended to other relevant nuclei in the future, providing solid ground for the prediction of the antineutrino spectrum in reactors.

Estimating confidence intervals in small or noisy datasets is a challenge in biomolecular research when data contain outliers or high variability. We introduce a robust method combining a hybrid bootstrap procedure with Steiner's most frequent value (MFV) approach to estimate confidence intervals without removing outliers or altering the dataset. The MFV identifies the most representative value while minimizing information loss, ideal for limited or non-Gaussian samples. To demonstrate robustness, we apply the MFV-hybrid parametric bootstrapping (MFV-HPB) framework to the fast-neutron activation cross-section of the 109Ag(n,2n)108mAg reaction, a nuclear physics dataset with large uncertainties and evaluation difficulties. Repeated resampling and uncertainty-based simulations yield a robust MFV of 709 mb with a 68.27% confidence interval of [691, 744] mb, illustrating the method's interpretability in complex scenarios. Although the example is from nuclear science, similar issues arise in enzymatic kinetics, molecular assays, and biomarker studies. The MFV-HPB framework offers a generalizable approach for extracting central estimates and confidence intervals in small or noisy datasets, with resilience to outliers, minimal distributional assumptions, and suitability for small samples-making it valuable in molecular medicine, bioengineering, and biophysics.

As the LHC beams cannot be polarized, introducing a dense polarized gas target at the LHCb experiment at CERN, to be operated concurrently with beam-beam collisions, will facilitate fixed-target interactions to explore a new energy regime of spin physics measurements. Unfortunately, typical surface coatings, such as water, Teflon, or aluminum, commonly used to avoid polarization losses, are prohibited due to restrictions imposed by vacuum and beam policies. Using the former atomic beam source for the polarized target at ANKE/COSY (Forschungszentrum J\"ulich), an accompanying Lamb-shift polarimeter and a storage cell chamber inside a superconducting magnet, provide a perfect test stand to investigate the properties of a storage cell coated with amorphous carbon. A significant recombination rate, ranging from $93\%$ to $100\%$, as well as preservation of polarization during recombination surpassing $74\%$, were observed. We successfully produced H$_2$ molecules with a nuclear polarization of P$\sim 0.59$. In addition, we could produce polarized H$_3^+$ ions for the first time and observed the shift of the axis of rotation within HD molecules.

We present a calculation of the leading two-loop corrections to the axial-vector coupling constant $g_A$ in two covariant versions of two-flavor baryon chiral perturbation theory. Taking the low-energy constants from a combined analysis of elastic and inelastic pion-nucleon scattering, we find that these corrections are rather moderate.

The Neutrinos from Stored Muons, nuSTORM, facility has been designed to deliver a definitive neutrino-nucleus scattering programme using beams of ,{\nu}e- and ,{\nu}{\mu}- from the decay of muons confined within a storage ring. The facility is unique, it will be capable of storing {\mu} beams with a central momentum of between 1 GeV/c and 6 GeV/c and a momentum spread of 16%. This specification will allow neutrino-scattering measurements to be made over the kinematic range of interest to the DUNE and Hyper-K collaborations. At nuSTORM, the flavour composition of the beam and the neutrino-energy spectrum are both precisely known. The storage-ring instrumentation will allow the neutrino flux to be determined to a precision of 1% or better. With its existing proton-beam infrastructure, CERN is uniquely well-placed to implement nuSTORM. A summary of the proposed implementation of nuSTORM at CERN is presented below.