In a recent paper (2024) M. Buratti and M.E:Muzychuck have established some lower bounds on the number of non isomorphic cyclic Steiner Triple Systems of order $v\equiv 1$ (mod $6$). We complete their result to the case $v\equiv 3$ (mod $6$). For each odd $k > 3$ we also find lower bounds for the number of non isomorphic cyclic $k$-cycle systems of a complete graph.

In this paper, we investigate the counter-forensic effects of the new JPEG AI standard based on neural image compression, focusing on two critical areas: deepfake image detection and image splicing localization. Neural image compression leverages advanced neural network algorithms to achieve higher compression rates while maintaining image quality. However, it introduces artifacts that closely resemble those generated by image synthesis techniques and image splicing pipelines, complicating the work of researchers when discriminating pristine from manipulated content. We comprehensively analyze JPEG AI's counter-forensic effects through extensive experiments on several state-of-the-art detectors and datasets. Our results demonstrate a reduction in the performance of leading forensic detectors when analyzing content processed through JPEG AI. By exposing the vulnerabilities of the available forensic tools, we aim to raise the urgent need for multimedia forensics researchers to include JPEG AI images in their experimental setups and develop robust forensic techniques to distinguish between neural compression artifacts and actual manipulations.

The angular distribution of gravitational-wave power from persistent sources may exhibit anisotropies arising from the large-scale structure of the Universe. This motivates directional searches for astrophysical and cosmological gravitational-wave backgrounds, as well as continuous-wave emitters. We present results of such a search using data from the first observing run through the first portion of the fourth observing run of the LIGO-Virgo-KAGRA Collaborations. We apply gravitational-wave radiometer techniques to generate skymaps and search for both narrowband and broadband persistent gravitational-wave sources. Additionally, we use spherical harmonic decomposition to probe spatially extended sources. No evidence of persistent gravitational-wave signals is found, and we set the most stringent constraints to date on such emissions. For narrowband point sources, our sensitivity estimate to effective strain amplitude lies in the range $(0.03 - 8.4) \times 10^{-24}$ across all sky and frequency range $(20 - 160)$ Hz. For targeted sources -- Scorpius X-1, SN 1987A, the Galactic Center, Terzan 5, and NGC 6397 -- we constrain the strain amplitude with best limits ranging from $\sim 1.1 \times 10^{-25}$ to $6.5 \times 10^{-24}$. For persistent broadband sources, we constrain the gravitational-wave flux F_{\alpha, \hat{n}}^{95\%, \mathrm{UL}}(25\, \mathrm{Hz}) < (0.008 - 5.5) \times 10^{-8}\, \mathrm{erg\, cm^{-2}\, s^{-1}\, Hz^{-1}}, depending on the sky direction $\hat{n}$ and spectral index $\alpha=0,\,2/3,\,3$. Finally, for extended sources, we place upper limits on the strain angular power spectrum C_\ell^{1/2} < (0.63 - 17) \times 10^{-10} \,\mathrm{sr}^{-1}.

Explainable AI (XAI) has been investigated for decades and, together with AI itself, has witnessed unprecedented growth in recent years. Among various approaches to XAI, argumentative models have been advocated in both the AI and social science literature, as their dialectical nature appears to match some basic desirable features of the explanation activity. In this survey we overview XAI approaches built using methods from the field of computational argumentation, leveraging its wide array of reasoning abstractions and explanation delivery methods. We overview the literature focusing on different types of explanation (intrinsic and post-hoc), different models with which argumentation-based explanations are deployed, different forms of delivery, and different argumentation frameworks they use. We also lay out a roadmap for future work.

Sound-squatting is a phishing attack that tricks users into malicious resources by exploiting similarities in the pronunciation of words. Proactive defense against sound-squatting candidates is complex, and existing solutions rely on manually curated lists of homophones. We here introduce Sound-skwatter, a multi-language AI-based system that generates sound-squatting candidates for proactive defense. Sound-skwatter relies on an innovative multi-modal combination of Transformers Networks and acoustic models to learn sound similarities. We show that Sound-skwatter can automatically list known homophones and thousands of high-quality candidates. In addition, it covers cross-language sound-squatting, i.e., when the reader and the listener speak different languages, supporting any combination of languages. We apply Sound-skwatter to network-centric phishing via squatted domain names. We find ~ 10% of the generated domains exist in the wild, the vast majority unknown to protection solutions. Next, we show attacks on the PyPI package manager, where ~ 17% of the popular packages have at least one existing candidate. We believe Sound-skwatter is a crucial asset to mitigate the sound-squatting phenomenon proactively on the Internet. To increase its impact, we publish an online demo and release our models and code as open source.

In automated planning, recognising the goal of an agent from a trace of observations is an important task with many applications. The state-of-the-art approaches to goal recognition rely on the application of planning techniques, which requires a model of the domain actions and of the initial domain state (written, e.g., in PDDL). We study an alternative approach where goal recognition is formulated as a classification task addressed by machine learning. Our approach, called GRNet, is primarily aimed at making goal recognition more accurate as well as faster by learning how to solve it in a given domain. Given a planning domain specified by a set of propositions and a set of action names, the goal classification instances in the domain are solved by a Recurrent Neural Network (RNN). A run of the RNN processes a trace of observed actions to compute how likely it is that each domain proposition is part of the agent's goal, for the problem instance under considerations. These predictions are then aggregated to choose one of the candidate goals. The only information required as input of the trained RNN is a trace of action labels, each one indicating just the name of an observed action. An experimental analysis confirms that \our achieves good performance in terms of both goal classification accuracy and runtime, obtaining better performance w.r.t. a state-of-the-art goal recognition system over the considered benchmarks.

Inclusive electron scattering cross sections off a hydrogen target at a beam energy of 10.6 GeV have been measured with data collected from the CLAS12 spectrometer at Jefferson Laboratory. These first absolute cross sections from CLAS12 cover a wide kinematic area in invariant mass W of the final state hadrons from the pion threshold up to 2.5 GeV for each bin in virtual photon four-momentum transfer squared $Q^2$ from 2.55 to 10.4~GeV$^2$ owing to the large scattering angle acceptance of the CLAS12 detector. Comparison of the cross sections with the resonant contributions computed from the CLAS results on the nucleon resonance electroexcitation amplitudes has demonstrated a promising opportunity to extend the information on their $Q^2$ evolution up to 10 GeV$^2$. Together these results from CLAS and CLAS12 offer good prospects for probing the nucleon parton distributions at large fractional parton momenta $x$ for $W$ < 2.5 GeV, while covering the range of distances where the transition from the strongly coupled to the perturbative regimes is expected.

In automated planning, control parameters extend standard action representations through the introduction of continuous numeric decision variables. Existing state-of-the-art approaches have primarily handled control parameters as embedded constraints alongside other temporal and numeric restrictions, and thus have implicitly treated them as additional constraints rather than as decision points in the search space. In this paper, we propose an efficient alternative that explicitly handles control parameters as true decision points within a systematic search scheme. We develop a best-first, heuristic search algorithm that operates over infinite decision spaces defined by control parameters and prove a notion of completeness in the limit under certain conditions. Our algorithm leverages the concept of delayed partial expansion, where a state is not fully expanded but instead incrementally expands a subset of its successors. Our results demonstrate that this novel search algorithm is a competitive alternative to existing approaches for solving planning problems involving control parameters.

The observation of beam spin asymmetries in two-pion production in semi-inclusive deep inelastic scattering off an unpolarized proton target is reported. The data presented here were taken in the fall of 2018 with the CLAS12 spectrometer using a 10.6 GeV longitudinally spin-polarized electron beam delivered by CEBAF at JLab. The measured asymmetries provide the first opportunity to extract the parton distribution function $e(x)$, which provides information about the interaction between gluons and quarks, in a collinear framework that offers cleaner access than previous measurements. The asymmetries also constitute the first ever signal sensitive to the helicity-dependent two-pion fragmentation function $G_1^\perp$. A clear sign change is observed around the $\rho$ mass that appears in model calculations and is indicative of the dependence of the produced pions on the helicity of the fragmenting quark.

Although the automatic identification of the optimal fingering for the performance of melodies on fretted string instruments has already been addressed (at least partially) in the literature, the specific case regarding lead electric guitar requires a dedicated approach. We propose a system that can generate, from simple MIDI melodies, tablatures enriched by fingerings, articulations, and expressive techniques. The basic fingering is derived by solving a constrained and multi-attribute optimization problem, which derives the best position of the fretting hand, not just the finger used at each this http URL, by analyzing statistical data from the mySongBook corpus, the most common clich{é}s and biomechanical feasibility, articulations, and expressive techniques are introduced. Finally, the obtained output is converted into MusicXML format, which allows for easy visualization and use. The quality of the tablatures derived and the high configurability of the proposed approach can have several impacts, in particular in the fields of instrumental teaching, assisted composition and arranging, and computational expressive music performance models.

The aim of the paper is to derive spectral estimates into several classes of magnetic systems. They include three-dimensional regions with Dirichlet boundary as well as a particle in $\mathbb{R}^3$ confined by a local change of the magnetic field. We establish two-dimensional Berezin-Li-Yau and Lieb-Thirring-type bounds in the presence of magnetic fields and, using them, get three-dimensional estimates for the eigenvalue moments of the corresponding magnetic Laplacians.

The term material with memory is generally used to indicate materials whose mechanical and/or thermodynamical behaviour depends not only on the process at the present time but also on the history of the process itself. Crucial in heat conductors with memory is the heat relaxation function which models the thermal response of the material. The present study is concerned about a thermodynamical problem with memory "aging"; that is, we analyze the temperature evolution within a rigid heat conductor with memory whose relaxation function takes into account the aging of the material. In particular, we account for variations of the relaxation function due to a possible deterioration of the thermal response of the material related to its age.

In this paper we investigate the validity of first and second order $L^{p}$ estimates for the solutions of the Poisson equation depending on the geometry of the underlying manifold. We first present $L^{p}$ estimates of the gradient under the assumption that the Ricci tensor is lower bounded in a local integral sense and construct the first counterexample showing that they are false, in general, without curvature restrictions. Next, we obtain $L^p$ estimates for the second order Riesz transform (or, equivalently, the validity of $L^{p}$ Calder\'on--Zygmund inequalities) on the whole scale $1

Given a group G and positive integers k,n, we let B_n=B_n(G) denote the set of all elements x in G such that |x^G|\leq n, and we say that G satisfies the (k,n)-covering condition for commutators if there is a subset S in G such that |S|\leq k and all commutators of G are contained in the product SB_n. The importance of groups satisfying this condition was revealed in the recent study of probabilistically nilpotent finite groups of class two. The main result obtained in this paper is the following theorem. Let G be a group satisfying the (k,n)-covering condition for commutators. Then G' contains a characteristic subgroup B such that [G':B] and |B'| are both (k,n)-bounded. This extends several earlier results of similar flavour.

A Steiner triple system STS$(v)$ is called $f$-pyramidal if it has an automorphism group fixing $f$ points and acting sharply transitively on the remaining ones. In this paper, we focus on the STSs that are $f$-pyramidal over some abelian group. Their existence has been settled only for the smallest admissible values of $f$, that is, $f=0,1,3$. In this paper, we complete this result and determine, for every $f>3$, the spectrum of values $(f,v)$ for which there is an $f$-pyramidal STS$(v)$ over an abelian group. This result is obtained by constructing difference families relative to a suitable partial spread.

Pontecorvo reactions are rare antinucleon annihilation processes that are forbidden on free nucleons but allowed on nucleons bound within nuclei. The interest in studying this phenomenon lies in its potential to provide insights into the annihilation mechanism and, particularly, the short-distance dynamics between nucleons within the nucleus. Some measurements were performed in the past at CERN's Low Energy Antiproton Ring (LEAR) using antiprotons annihilating on a deuterium target. However, no data exist for targets consisting of three nucleons, such as $^3\text{He}$ or $^3\text{H}$. The measurement of the rate of the process $\overline{p} \, ^3\text{He} \rightarrow p + n$ would allow for distinguishing between different theoretical models whose predictions vary by 1-2 orders of magnitude. The ASACUSA collaboration is studying the feasibility of performing this measurement at CERN's ELENA-AD. A preliminary design of a simple measurement apparatus, utilizing plastic scintillators and degrader layers, is presented, together with Monte Carlo simulations assessing its efficiency in measuring the branching ratios of the aforementioned reaction and rejecting background from more probable typical antiproton annihilations in the target.

A study of antiproton annihilations at rest on thin solid targets is underway at the ASACUSA facility, which now features a dedicated beam line for slow extraction at 250 eV. The experiment will employ new technologies, such as the Timepix4 ASICs coupled to silicon sensors, to measure the total multiplicity, energy, and angular distribution of various prongs produced in thin solid targets. A detection system consisting of seven Timepix4, covering most of the solid angle, is being constructed. A 3D annihilation vertex reconstruction algorithm from particle tracks in the single-plane detectors has been developed using Monte Carlo simulations. The measurements will enable a study of pbar-nucleus interactions, their dependence on nucleus mass and branching ratios. The results will be used to assess and potentially improve various simulation models.

Extensive data of antiproton scattering cross sections with protons and nuclei have advanced our understanding of hadronic interactions with antinucleons. However, low-energy antineutron scattering data are scarce, thereby limiting our understanding of the S-wave antinucleon-nucleon and antinucleon-nucleus interactions. We present a novel production scheme of extremely low-energy antineutrons that could remedy this situation. This method is based on backward charge-exchange reaction ($p\bar{p}\to n\bar{n}$), and can reach the lowest momentum of 9 MeV/c, which would be well suited to study of the S-wave antinucleon-nucleon or antinucleon-nucleus interactions.

The results presented in this paper are a natural development of those described in the paper {\it The Volterra Integrable case. Novel analytical and numerical results} (OCNMP Vol.4 (2024) pp 188-211), where the authors reconsidered the integrable case of the Hamiltonian $N$-species Lotka-Volterra system, introduced by Vito Volterra in 1937. There, an alternative approach for constructing the integrals of motion has been proposed, and compared with the old Volterra approach. Here we go beyond, and show that in fact the model introduced by Volterra and studied by us is not just integrable, but is maximally superintegrable and reducible to a system with only one degree of freedom regardless the number of species considered. We present both analytical and numerical results.