Search Results (158)

The introduction of axions gives rise to additional one-loop diagrams for the two-photon decays of neutral pions via axion-pion mixing. We compute this correction that has been overlooked in existing calculations, within the framework of SU(2) chiral perturbation theory. Our analysis shows that the correction is proportional to the axion-photon coupling and the square of the axion mass. In the classical axion parameter space, this correction is strongly suppressed by the axion decay constant. However, for QCD axions in the MeV or higher mass range, the correction may become significant. Furthermore, when combined with experimental measurements of the decay width of the ${\pi }^0\to \gamma \gamma$ process, our results rule out the standard QCD axion as a viable explanation for the observed discrepancy between chiral perturbation theory predictions and experimental data. Full article

As neutrino experiments enter the precision era, it is desirable to identify any deviation between data and theoretical predictions and to provide possible models as explanation. Particularly useful is the description in terms of non-standard interactions (NSIs), which can be related to neutral (NC-NSI) or charged (CC-NSI) currents. Previously, we have developed the code eft-neutrino that connects NSI with generic ultraviolet (UV) models at tree-level matching. In this work, we integrate our code with other tools, increasing the matching between the UV and infrared (IR) theories to a one-loop level. As a working example, we consider the pion and kaon decay, the main production mechanisms in accelerator neutrino experiments. We provide up-to-date allowed regions on a set of Wilson coefficients related to pion and kaon decay. We also illustrate how our chain of codes can be applied to particular UV models, showing that a seemingly large allowed CC-NSI value can be significantly reduced when considering a specific UV model. Full article

In this paper, I investigate the gluon distributions for the kaon and pion, as well as the improvement of the valence-quark distributions, in the framework of the gauge-invariant nonlocal chiral quark model (NL$\chi$QM), where the momentum dependence is taken into account. I then compute the gluon distributions for the kaon and pion that are dynamically generated from the splitting functions in the Dokshitzer–Gribov–Lipatov–Altarelli–Parisi (DGLAP) QCD evolution. In a comparison with the recent lattice QCD and JAM global analysis results, it is found that the results for the pion gluon distributions at $Q=$ 2 GeV, which is set based on the lattice QCD, have a good agreement with the recent lattice QCD data; this is followed up with the up valence-quark distribution of the pion results at $Q=$ 5.2 GeV in comparison with the reanalysis experimental data. The prediction for the kaon gluon distributions at $Q=2$ GeV is consistent with the recent lattice QCD calculation. Full article

In ultra-relativistic heavy-ion collisions, the study of muons from kaon (K) and pion ($\pi$) decays provides insights into hadron production and propagation in the Quark–Gluon Plasma (QGP). This paper investigates muon yields from K and $\pi$ decays in Pb–Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV using a fast simulation method. We employ a fast Monte Carlo procedure to estimate muon yields from charged kaons and pions. The simulation involves generating pions and kaons with uniform $p_{\mathrm{T}}$ and y distributions, simulating their decay kinematics via PYTHIA, and reweighting to match the physical spectra. Our results show the transverse momentum distributions of muons from K and $\pi$ decays at forward rapidity ($2.5<y<4.0$) for different centrality classes. The systematic uncertainties are primarily from the mid-rapidity charged K/$\pi$ spectra and rapidity-dependent $R_{\mathrm{AA}}$ uncertainties. The muon yields from pion and kaon decays exhibit consistency across centrality classes in the $p_{\mathrm{T}}$ range of 3–10 GeV/c. This study contributes to understanding hadronic interactions and decay kinematics in heavy-ion collisions, offering references for investigating pion and kaon decay channels and hot medium effects. Full article

Background: This study delves into the potential use of real-time UV imaging of the dissolution process combined with convolutional neural networks (CNNs) to develop multidimensional models representing the relation between in vitro and in vivo performance of drugs. Method: We utilised the capabilities of the SDi2 apparatus (Pion) to capture multidimensional dissolution data for two distinct Glucophage tablets: immediate-release 500 mg tablets and extended-release 750 mg tablets. The dissolution process was studied in various media, including a compendial pH 1.2 HCl solution, reverse osmosis water, and pH 6.8 phosphate buffer. Result: Moreover, results were captured at different wavelengths (255 nm and 520 nm) to provide a comprehensive view of the process. Our investigation focuses on two primary approaches: (1) analysing numerical data extracted from SDi2 images via a surface characterisation tool, using traditional machine learning techniques, including Scikit-learn, Tensorflow, and AutoML, and (2) utilising raw SDi2 images to train CNNs for direct prediction of in vivo metformin plasma concentrations. Conclusions: This dual approach allows us to assess the impact of data extraction on model performance and explore the potential of CNNs to capture complex dissolution patterns directly from images, potentially revealing hidden information not captured by traditional numerical data extraction methods. Full article

In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a homogeneous lead tungstate calorimeter with high transverse and longitudinal segmentation, we investigated the discrimination of protons, positive pions, and positive kaons at 100 GeV. The analysis focuses on the impact of calorimeter granularity by progressively merging detector cells and extracting features like energy deposition patterns and timing information. Two machine learning approaches, XGBoost and fully connected deep neural networks, were employed to assess the classification performance across particle pairs. The results indicate that fine segmentation improves particle discrimination, with higher granularity yielding more detailed characterization of energy showers. Additionally, the results highlight the importance of shower radius, energy fractions, and timing variables in distinguishing particle types. The XGBoost model demonstrated computational efficiency and interpretability advantages over deep learning for tabular data structures, while achieving similar classification performance. This motivates further work required to combine high- and low-level feature analysis, e.g., using convolutional and graph-based neural networks, and extending the study to a broader range of particle energies and types. Full article

Background: The bioavailability of a drug depends, among other parameters, on solubility. One of the strategies used to enhance the solubility of sparingly soluble drugs is the use of excipients. Excipients can interact with the drug by increasing its solubility and/or stabilizing supersaturated solutions. Some of the most common excipients are cyclodextrins and hydrophilic polymers. Objectives: The effect of two cyclodextrins (captisol and cavasol) and three hydrophilic polymers (klucel, kollidon and plasdone S630) on the solubility of three ionizable drugs (benzthiazide, isoxicam, and piroxicam) is evaluated at biorelevant pH values, using two complementary techniques. Methods: The solubility enhancement was evaluated by the comparison of the solubility with and without the presence of excipients through the shake-flask and CheqSol methodology. Results: Captisol and cavasol slightly increase the concentration of the neutral species of the drugs in the solution before precipitation begins, although they do not enhance the supersaturation duration nor the thermodynamic solubility of the drugs. The increase in solubility in the presence of cyclodextrins is mainly caused by the ionization state of the drug. Hydrophilic polymers not only improve thermodynamic solubility but also the extent and the duration of the supersaturation. Some metastable forms are observed for benzthiazide and isoxicam in the presence of kollidon and plasdone S630. Conclusions: The shake-flask method enabled the evaluation of thermodynamic solubility both in the absence and presence of excipients. Meanwhile, the CheqSol method provided insights into the presence of supersaturated solutions. Different behavior is observed depending on the nature of the excipient. Full article

Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics processes has traditionally posed a significant challenge. In this work, we introduce the end-to-end. AI Detector Optimization framework (AIDO), which leverages a diffusion model as a surrogate for the full simulation and reconstruction chain, enabling gradient-based design exploration in both continuous and discrete parameter spaces. Although this framework is applicable to a broad range of detectors, we illustrate its power using the specific example of a sampling calorimeter, focusing on charged pions and photons as representative incident particles. Our results demonstrate that the diffusion model effectively captures critical performance metrics for calorimeter design, guiding the automatic search for a layer arrangement and material composition that align with known calorimeter principles. The success of this proof-of-concept study provides a foundation for the future applications of end-to-end optimization to more complex detector systems, offering a promising path toward systematically exploring the vast design space in next-generation experiments. Full article

The hadronic phase and its dynamics in relativistic heavy-ion collisions are topics of immense discussion. The hadronic phase contains various massive hadrons with an abundance of the lightest hadron, i.e., $\pi$-mesons (pions). In this paper, we consider that pions are in the thermal equilibrium in the hadronic phase and use second-order viscous hydrodynamics for a medium of massive pions to obtain its expansion to the boundary of the kinetic freeze-out. We achieve the kinetic freeze-out boundary with the Knudsen number $\mathrm{Kn}>1$ limit. When this condition is met, hydrodynamics expansion breaks down, and the mean free path becomes sufficiently large in comparison with the system size so that the particle yields are preserved. Further, we investigate the effect of the massive fluid on the resonance particle yields, including re-scattering and regeneration, along with the natural decay widths of the resonances. The resonances can play an essential role in determining the characteristics of the hadronic phase as they have sufficiently small lifetimes, which may be comparable to the hadronic phase lifetime. In the current study, we predict the hadronic phase lifetime, which is further used to determine the $K^{*}{\left(892\right)}^0/K$, $\varphi \left(1020\right)/K$, and $\rho {\left(770\right)}^0/\pi$ yield ratios at the kinetic freeze-out. We calculate these ratios as a function of charged particle multiplicity and transverse momentum and compare the findings with experimental data. Our calculations qualitatively agree with the experimental data, indicating a possible hydrodynamical evolution of the hadronic phase. Full article

Our objective is to test the published models of partonic energy loss, particularly those describing the energy loss mechanisms of quarks traversing nuclear matter, within the framework of semi-inclusive deep inelastic scattering. Our methodological approach focuses on quantifying the quark energy loss in cold matter by analyzing the positive pions (${\pi }^{+}$) produced in various nuclear targets, including deuterium, carbon, iron and lead, while our first approach only includes deuterium and carbon. Before normalizing the pions’ energy distribution to unity to perform a shape analysis, acceptance corrections were performed to account for the detector’s efficiency and ensure accurate comparisons of the spectra. By normalizing the energy spectra of ${\pi }^{+}$ produced from these distinct targets and based on the Baier–Dokshitzer–Mueller–Peigné–Schiff theory, which posits that quark energy loss depends only on nuclear size, it is assumed that the energy distributions of the targets will exhibit similar behavior. For this normalization, an energy shift between these distributions, corresponding to the quark energy loss, is identified. To ensure accuracy, statistical techniques such as the Kolmogorov–Smirnov test are used. The data used to test and explore the analysis technique and method were from the CLAS6 EG2 dataset collected using Jefferson Lab’s CLAS detector. Full article

Most novel active pharmaceutical ingredients have low water solubility; therefore, solubility-enhancing methods are applied. The aim of the present investigation is to study the impact of nine commonly used pharmaceutical excipients (fillers, surfactants, cyclodextrins, polymers) on solubility, permeability and their relationship. This is crucial for ensuring optimal bioavailability. Carbamazepine, naproxen and pimobendan were chosen as model compounds due to their different acid–base properties. Equilibrium solubility was measured by the traditional shake flask method. Effective permeability was determined by the PAMPA model. Measurements of ionizable compounds were carried out at three pH values. The pH-dependent change in the investigated parameters is maintained even in the presence of excipients. Fillers resulted in a slight or no effect, while the impact of other excipients showed a significant concentration dependence. The impact of excipients was influenced by the structure and ionization state of the molecules. The dominance of the ionized form moderates the impact of excipients. The changes in solubility were more pronounced than in the case of permeability. By examining the effect of the ionization state and interactions with excipients, this work supports the development of formulations that enhance solubility with minimal impacts on permeability. Additionally, it can serve as good basis for preformulation studies and design optimization. Full article

Failure of anti-TNF therapy is a real concern in children with inflammatory bowel disease (IBD) owing to the limited therapeutic arsenal. Anti-TNF drugs modulate the immune response, a key driver of chronic inflammation in IBD. Accordingly, we analyzed changes in the frequency of T-lymphocyte and cytokine levels after 6 weeks of treatment to identify potential biomarkers of response to anti-TNF drugs. We recruited 77 patients under 18 years of age diagnosed with IBD and treated with an anti-TNF drug. Using flow cytometry and multiplex ELISA, we analyzed 31 T-lymphocyte populations and four cytokines. We identified changes in 10 populations of T lymphocytes after 6 weeks of treatment. Naïve Tregs were associated with a primary response to anti-TNF drugs, while activated Tregs were associated with long-term response. Serum INF-γ levels were decreased after anti-TNF treatment in children with Crohn’s disease (CD), but not in those with ulcerative colitis (UC). The memory CD8+ Type 2 Cytotoxic T (Tc2) subset increased in non-responders with CD and the CD4+ memory Th17 cells increased in non-responders with UC. These findings could help us to understand the cellular regulation of anti-TNF therapy, to identify children at a higher risk of treatment failure, and, potentially, to develop more personalized therapeutic strategies. Full article

Magnetic monopoles, though elusive as elementary particles, emerge as quantum excitations in granular quantum materials. Under certain conditions, they can undergo Bose condensation, leading to the formation of a novel state of matter known as the superinsulator. In this state, charge carriers, Cooper pairs and anti-Cooper pairs, are bound together by an electric flux string, forming neutral electric pions. This confinement mechanism results in an infinite resistance that persists even at finite temperatures. Superinsulators behave, thus, as dual superconductors. Full article

In this paper, we describe the study of one- and three-dimension pion and kaon source functions for chaotic and partially coherent sources in Pb-Pb central collisions at $\sqrt{s_{NN}}=2.76$ TeV using the AMPT model. The characteristic source function quantities are calculated and compared with the results obtained by fitting the two-boson correlation functions using the Gaussian source formula. It was found that the imaging results are approximately consistent with the results of the Gaussian source formula fits. The partially coherent pion sources exhibit a high degree of coherence. However, the kaon pairs with high transverse momenta are emitted with a high degree of chaos. Full article

The gauge covariance of the quark gap equation is compared for the case of three different quark–gluon vertices: the bare vertex, a Ball–Chiu-like vertex constrained by the corresponding Slavnov–Taylor identity, and a full vertex including the transverse components derived from transverse Slavnov–Taylor identities. The covariance properties are verified with the chiral quark condensate and the pion decay constant in the chiral limit. Full article