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This article presents a review about the main CERN n\_TOF contributions to the field of neutron-capture experiments of interest for $s$-process nucleosynthesis studies over the last 25 years, with special focus on the measurement of radioactive isotopes. A few recent capture experiments on stable isotopes of astrophysical interest are also discussed. Results on $s$-process branching nuclei are appropriate to illustrate how advances in detection systems and upgrades in the facility have enabled increasingly challenging experiments and, as a consequence, have led to a better understanding and modeling of the $s$-process mechanism of nucleosynthesis. New endeavors combining radioactive-ion beams from ISOLDE for the production of radioisotopically pure samples for activation experiments at the new NEAR facility at n\_TOF are briefly discussed. On the basis of these new exciting results, also current limitations of state-of-the-art TOF and activation techniques will be depicted, thereby showing the pressing need for further upgrades and enhancements on both facilities and detection systems. A brief account of the potential technique based on inverse kinematics for direct neutron-capture measurements is also presented., Comment: submitted to Eur. Phys. Jour. Topical Collection

Nonlinear molecular excitations in DNA have traditionally been modelled using the nonlinear Schr\"odinger equation (NLSE). An alternative approach is based on the plane-base rotator model and the SU(2)/U(1) generalized spin coherent states, which leads to a cubic quintic NLSE. Higher-order nonlinearities are particularly useful for modelling complex interactions, such as those in DNA-protein systems, where multiple competing forces play a significant role. Additionally, the surrounding viscous medium introduces dissipative forces that affect the propagation of molecular excitations, leading to energy dissipation and damping effects. These damping effects are modelled using the quasi-stationary method, which describes the system's near-equilibrium behaviour. In this work, we explore the evolution of nonlinear molecular excitations in DNA-protein systems, accounting for damping effects, and discuss potential applications to the transcription process.

Challenging neutron-capture cross-section measurements of small cross sections and samples with a very limited number of atoms require high-flux time-of-flight facilities. In turn, such facilities need innovative detection setups that are fast, have low sensitivity to neutrons, can quickly recover from the so-called $\gamma$-flash, and offer the highest possible detection sensitivity. In this paper, we present several steps toward such advanced systems. Specifically, we describe the performance of a high-sensitivity experimental setup at CERN n\_TOF EAR2. It consists of nine sTED detector modules in a compact cylindrical configuration, two conventional used large-volume C$_{6}$D$_{6}$ detectors, and one LaCl$_{3}$(Ce) detector. The performance of these detection systems is compared using $^{93}$Nb($n$,$\gamma$) data. We also developed a detailed \textsc{Geant4} Monte Carlo model of the experimental EAR2 setup, which allows for a better understanding of the detector features, including their efficiency determination. This Monte Carlo model has been used for further optimization, thus leading to a new conceptual design of a $\gamma$ detector array, STAR, based on a deuterated-stilbene crystal array. Finally, the suitability of deuterated-stilbene crystals for the future STAR array is investigaged experimentally utilizing a small stilbene-d12 prototype. The results suggest a similar or superior performance of STAR with respect to other setups based on liquid-scintillators, and allow for additional features such as neutron-gamma discrimination and a higher level of customization capability.

We analyze how neutrino oscillation and coherent elastic neutrino-nucleus scattering data impact the global SMEFT fit. We first review the mapping between the SMEFT parameters and the so-called NSI framework, commonly considered in the neutrino literature. We also present a detailed discussion of how the measurements for the normalization of neutrino fluxes and cross sections, that will also be affected by the new physics, indirectly impact the measured oscillation probabilities. We then analyze two well-motivated simplified scenarios. Firstly, we study a lepton flavour conserving case, usually assumed in global SMEFT analyses, showing the complementarity of neutrino oscillation and CE$\nu$NS experiments with other low-energy observables. We find that the inclusion of neutrino data allows to constrain previously unbounded SMEFT operators involving the tau flavour and confirm the improvement of the constraint on a combination of Wilson coefficients previously identified. Moreover, we find that neutrino oscillation constraints on NSI are improved when embedded in the global SMEFT framework. Secondly, we study a lepton flavour violating scenario and find that neutrino data also improves over previously derived global constraints thanks to its sensitivity to new combinations of Wilson coefficients., Comment: 25 pages + Appendix

The emergence of the open radio access network (O-RAN) architecture offers a paradigm shift in cellular network management and service orchestration, leveraging data-driven, intent-based, autonomous, and intelligent solutions. Within O-RAN, the service management and orchestration (SMO) framework plays a pivotal role in managing network functions (NFs), resource allocation, service provisioning, and others. However, the increasing complexity and scale of O-RANs demand autonomous and intelligent models for optimizing SMO operations. To achieve this goal, it is essential to integrate intelligence and automation into the operations of SMO. In this manuscript, we propose three scenarios for integrating machine learning (ML) algorithms into SMO. We then focus on exploring one of the scenarios in which the non-real-time RAN intelligence controller (Non-RT RIC) plays a major role in data collection, as well as model training, deployment, and refinement, by proposing a centralized ML architecture. Finally, we identify potential challenges associated with implementing a centralized ML solution within SMO.

The Heimburg-Jackson model, or thermodynamic soliton theory of nervous impulses, has a well-established record as an alternative model for studying the dynamics of nerve impulses and lipid bilayers. Within this framework, nerve impulses can be represented as nonlinear excitations of low amplitude depicted by the damped nonlinear Schr\"odinger equation and their adiabatic evolution can be analyzed using direct perturbative methods. Based on the foregoing, we carry out the current study using the quasi-stationary approach to obtain the adiabatic evolution of solitons embedded in lipid bilayers under the influence of a viscous elastic fluid. This analysis encompasses liquid-to-gel transition of the lipid bilayers, for whose dark and bright solitons arise, respectively.

Unlike expected from the Hodgkin-Huxley model predictions, in which there is annihilation once orthodromic and antidromic impulses collide, the Heimburg-Jackson model demonstrates that both impulses penetrate each other as it has been shown experimentally. These impulses can be depicted as low amplitude nonlinear excitations in a weakly dissipative soliton model described by the damped NLSE. In view of the above, the Karpman-Solov'ev-Maslov perturbation theory turns out to be ideal to study the interaction and adiabatic evolution of orthodromic and antidromic impulses once axoplasmic fluid is present.

Starting from the effective Hamiltonian arising from the tight binding model, we study the behaviour of low-lying excitations for bilayer graphene placed in periodic external magnetic fields by using irreducible second order supersymmetry transformations. The coupled system of equations describing these excitations is reduced to a pair of periodic Schr\"odinger Hamiltonians intertwined by a second order differential operator. The direct implementation of more general second-order supersymmetry transformations allows to create nonsingular Schr\"odinger potentials with periodicity defects and bound states embedded in the forbidden bands, which turn out to be associated to quasiperiodic magnetic superlattices. Applications in quantum metamaterials stem from the ability to engineer and control such bound states which could lead to a fast development of the subject in the near future.

Freezing of gait (FOG) is one of the most incapacitating symptoms in Parkinsons disease, affecting more than 50 percent of patients in advanced stages of the disease. The presence of FOG may lead to falls and a loss of independence with a consequent reduction in the quality of life. Wearable technology and artificial intelligence have been used for automatic FOG detection to optimize monitoring. However, differences between laboratory and daily-life conditions present challenges for the implementation of reliable detection systems. Consequently, improvement of FOG detection methods remains important to provide accurate monitoring mechanisms intended for free-living and real-time use. This paper presents advances in automatic FOG detection using a single body-worn triaxial accelerometer and a novel classification algorithm based on Transformers and convolutional networks. This study was performed with data from 21 patients who manifested FOG episodes while performing activities of daily living in a home setting. Results indicate that the proposed FOG-Transformer can bring a significant improvement in FOG detection using leave-one-subject-out cross-validation (LOSO CV). These results bring opportunities for the implementation of accurate monitoring systems for use in ambulatory or home settings.

We study in this paper optimal mass transport over a strongly connected, directed graph on a given discrete time interval. Differently from previous literature, we do not assume full knowledge of the initial and final goods distribution over the network nodes. In spite of the meager information, we show that it is possible to characterize the most likely flow in two important cases: The first one is when the initial and/or final distribution is only known on proper subsets of the nodes. The second case is when only some moments of the marginal distributions are known. As an important by-product, we determine the most likely initial and final marginals on the whole state space.

We consider a possible resummation of subleading effects in two-body systems with a large scattering length as described by a short-range effective field theory (EFT). In particular, we investigate the consequences of a resummation of part of the range corrections. Explicit calculations of the two-body phase shifts and charge form factor indicate that, except for extreme choices, resummations do not alter the convergence of the EFT expansion and are often beneficial at lowest orders. We have considered the expansion when the regulator cutoff is removed as well as when it is finite, and find that the cutoff is not an important factor for resummations. Our results connect with other works where the partial resummation is induced by potentials with finite cutoffs or interaction ranges., Comment: 11 pages, 7 figures

Complex networks have been studied in recent years due to their relevance in biological, social and technical real systems, such as the world wide web, social networks and biochemical interactions. One of the most current features of complex networks is the presence of (multi-)fractal properties. In spite of the amount of contributions that have been developed in fractal and multifractal analysis, all of them have focused on the adaptation of Fixed size algorithms (FSA) to complex networks, mostly box-counting and sandbox procedures. In this manuscript, a Fixed-mass algorithm (FMA) is adapted to explore the (multi-)fractality of unweighted complex networks is first proposed on the basis on a box-counting procedure. Thus, the aim of this work is to explore the applicability of a FMA to study fractal and multifractal characteristics of unweighted complex networks. After describing the proposed FMA for complex networks, it is tested in several kinds of complex networks such as deterministic, synthetic and real ones. Results suggest that FMA is able to adequately reproduce the fractal and multifractal properties of synthetic complex networks (scale-free, small-world and random). In addition, the algorithm is used for the multifractal description of real complex networks. The main advantage of FMA over FSA is that the minimum configuration of boxes (ideal) for completely covering the network is known. Therefore, results are quite precise when a reasonable covering configuration is obtained, allowing the reconstruction of the Mass exponent, {\tau} , and the Dimension function, D(q), with proper goodness-fits.

The interaction between dark matter and dark energy can be incorporated into field theory models of dark energy that have proved successful in alleviating the coincidence problem. We review recent advances in this field, including new models and constraints from different astronomical data sets. We show that interactions are allowed by observations and can reduce the current tensions among different measurements of cosmological parameters. We extend our discussion to include constraints from non-linear effects and results from cosmological simulations. Finally, we discuss forthcoming multi-messenger data from current and future observational facilities that will help to improve our understanding of the interactions within the dark sector., Comment: This review reports further advances in this field after we published our previous review article (Rept.Prog.Phys. 79 (2016) 9, 096901). It is accepted for publication in Reports on Progress in Physics

We introduce the notion of torsion-simple objects in an abelian category: these are the objects which are always either torsion or torsion-free with respect to any torsion pair. We present some general results concerning their properties, and then proceed to investigate the notion in various contexts, such as the category of modules over an artin algebra or a commutative noetherian ring, and the category of quasi-coherent sheaves over the projective line., Comment: 17 pages. Comments are welcome

Previous works have analysed the relationship existing between reference evapotranspiration (ET0) and other climatic variables under a one-at-a-time perturbation condition. However, due to the physical relationships between these climatic variables is advisable to study their joint influence on ET0. The box-counting joint multifractal algorithm describes the relations between variables using relevant information extracted from the data singularities. This work investigated the use of this algorithm to describe the simultaneous behaviour of ET0, calculated by means of Penman-Monteith (PM) equation, and relative humidity (RH) and air temperature (T), influencing on it in the middle zone of the Guadalquivir river valley, Andalusia, southern Spain. The studied cases were grouped according to the fractal dimension values, which were related to their probability of occurrence. The most likely cases were linked to smooth behaviour and weak dependence between variables, both circumstances were detected in the local multifractal analysis. For these cases, the rest of Penman Monteith (PM) equation variables, neither the T nor the RH, seemed to influence on ET0 determination, especially when low T values were involved. By contrast, the least frequent cases were those with variables showing high fluctuations and strong relationship between them. In these situations, when T is low, the ET0 is affected by the rest of PM equation variables. This fact confirmed T as main driver of ET0 because the higher T values the lesser influence of other climate variables on ET0. Joint multifractal analysis shows some limitations when it is applied to large number of variables, the results reported are promising and suggest the convenience of exploring the relationships between ET0 and other climatic variables not considered here with this framework such as wind speed and net radiation., Comment: 40 pages, 10 figures

Relying on the reverse-time space-time harmonic property of the ratio of two solutions of the Fokker-Plank equation, we establish an explicit formula for derivative of the \emph{varentropy} for a Markov diffusion process. The formula involves a nonlinear function of the {\em local free energy} $\ln(p_t(x)/\bar{p}(x))$.We then verify that our formula yields the correct result in the simple case of a scalar Gaussian diffusion. In the latter case, varentropy is exponentially decaying to zero.

One of the critical aspects for the accurate determination of neutron capture cross sections when combining time-of-flight and total energy detector techniques is the characterization and control of systematic uncertainties associated to the measuring devices. In this work we explore the most conspicuous effects associated to harsh count rate conditions: dead-time and pile-up effects. Both effects, when not properly treated, can lead to large systematic uncertainties and bias in the determination of neutron cross sections. In the majority of neutron capture measurements carried out at the CERN n\_TOF facility, the detectors of choice are the C$_{6}$D$_{6}$ liquid-based either in form of large-volume cells or recently commissioned sTED detector array, consisting of much smaller-volume modules. To account for the aforementioned effects, we introduce a Monte Carlo model for these detectors mimicking harsh count rate conditions similar to those happening at the CERN n\_TOF 20~m fligth path vertical measuring station. The model parameters are extracted by comparison with the experimental data taken at the same facility during 2022 experimental campaign. We propose a novel methodology to consider both, dead-time and pile-up effects simultaneously for these fast detectors and check the applicability to experimental data from $^{197}$Au($n$,$\gamma$), including the saturated 4.9~eV resonance which is an important component of normalization for neutron cross section measurements.

Neutron capture cross-section measurements are fundamental in the study of the slow neutron capture (s-) process of nucleosynthesis and for the development of innovative nuclear technologies. One of the best suited methods to measure radiative neutron capture (n,$\gamma$) cross sections over the full stellar range of interest for all the applications is the time-of-flight (TOF) technique. Overcoming the current experimental limitations for TOF measurements, in particular on low mass unstable samples, requires the combination of facilities with high instantaneous flux, such as the CERN n_TOF facility, with detection systems with an enhanced detection sensitivity and high counting rate capabilities. This contribution presents a summary about the recent highlights in the field of (n,$\gamma$) measurements at n_TOF. The recent upgrades in the facility and in new detector concepts for (n,\g) measurements are described. Last, an overview is given on the existing limitations and prospects for TOF measurements involving unstable targets and the outlook for activation measurements at the brand new high-flux n_TOF-NEAR station., Comment: 7 pages, 5 figures (8 panels). Proceedings of the CGS-17 conference. To be published in EPJ Web of Conferences

Based on recent data about the history of the Hubble factor, it is argued that the second law of thermodynamics holds at the largest scales accessible to observation. This is consistent with previous studies of the same question., Comment: 11 pages, 7 sets of figures, version accepted for publication in JCAP

A paradigm put forth by E. Schr\"odinger in 1931/32, known as Schr\"odinger bridges, represents a formalism to pose and solve control and estimation problems seeking a perturbation from an initial control schedule (in the case of control), or from a prior probability law (in the case of estimation), sufficient to reconcile data in the form of marginal distributions and minimal in the sense of relative entropy to the prior. In the same spirit, we consider traffic-flow and apply a Schr\"odinger-type dictum, to perturb minimally with respect to a suitable relative entropy functional a prior schedule/law so as to reconcile the traffic flow with scarce aggregate distributions on families of indistinguishable individuals. Specifically, we consider the problem to regulate/estimate multi-commodity network flow rates based only on empirical distributions of commodities being transported (e.g., types of vehicles through a network, in motion) at two given times. Thus, building on Schr\"odinger's large deviation rationale, we develop a method to identify {\em the most likely flow rates (traffic flow)}, given prior information and aggregate observations. Our method further extends the Schr\"odinger bridge formalism to the multi-commodity setting, allowing commodities to exit or enter the flow field as well (e.g., vehicles to enter and stop and park) at any time. The behavior of entering or exiting the flow field, by commodities or vehicles, is modeled by a Markov chains with killing and creation states. Our method is illustrated with a numerical experiment., Comment: 12 pages, 5 figures

We present an updated and improved global fit analysis of current flavor and electroweak precision observables to derive bounds on unitarity deviations of the leptonic mixing matrix and on the mixing of heavy neutrinos with the active flavours. This new analysis is motivated by new and updated experimental results on key observables such as $V_{ud}$, the invisible decay width of the $Z$ boson and the $W$ boson mass. It also improves upon previous studies by considering the full correlations among the different observables and explicitly calibrating the test statistic, which may present significant deviations from a $\chi^2$ distribution. The results are provided for three different Type-I seesaw scenarios: the minimal scenario with only two additional right-handed neutrinos, the next to minimal one with three extra neutrinos, and the most general one with an arbitrary number of heavy neutrinos that we parametrize via a generic deviation from a unitary leptonic mixing matrix. Additionally, we also analyze the case of generic deviations from unitarity of the leptonic mixing matrix, not necessarily induced by the presence of additional neutrinos. This last case relaxes some correlations among the parameters and is able to provide a better fit to the data. Nevertheless, inducing only leptonic unitarity deviations avoiding both the correlations implied by the right-handed neutrino extension as well as more strongly constrained operators is challenging and would imply significantly more complex UV completions., Comment: 27 pages + appendices, 7 figures, 7 tables

We consider the generation of a baryon asymmetry in an extension of the Standard Model with two singlet Majorana fermions that are degenerate above the electroweak phase transition. The model can explain neutrino masses as well as the observed matter-antimatter asymmetry, for masses of the heavy singlets below the electroweak scale. The only physical CP violating phases in the model are those in the PMNS mixing matrix, i.e. the Dirac phase and a Majorana phase that enter light neutrino observables. We present an accurate analytic approximation for the baryon asymmetry in terms of CP flavour invariants, and derive the correlations with neutrino observables. We demonstrate that the measurement of CP violation in neutrino oscillations as well as the mixings of the heavy neutral leptons with the electron, muon and tau flavours suffice to pin down the matter-antimatter asymmetry from laboratory measurements., Comment: 28 + 4 pages, 8 figures

Recently, the ANITA collaboration announced the detection of new, unsettling upgoing Ultra-High-Energy (UHE) events. Understanding their origin is pressing to ensure success of the incoming UHE neutrino program. In this work, we study their internal consistency and the implications of the lack of similar events in IceCube. We introduce a generic, simple parametrization to study the compatibility between these two observatories in Standard Model-like and Beyond Standard Model scenarios: an incoming flux of particles that interact with Earth nucleons with cross section $\sigma$, producing particle showers along with long-lived particles that decay with lifetime $\tau$ and generate a shower that explains ANITA observations. We find that the ANITA angular distribution imposes significant constraints, and when including null observations from IceCube only $\tau \sim 10^{-3}$ - $10^{-2} \,\mathrm{s}$ and $\sigma \sim 10^{-33}$ - $10^{-32}\,\mathrm{cm^2}$ can explain the data. This hypothesis is testable with future IceCube data. Finally, we discuss a specific model that can realize this scenario. Our analysis highlights the importance of simultaneous observations by high-energy optical neutrino telescopes and new UHE radio detectors to uncover cosmogenic neutrinos or discover new physics., Comment: 11 pages, 7 figures + Appendices. Comments welcome! v2: Added references and expanded the discussion on particle physics models. Matches version accepted by JHEP