Search

We analysed six primary transits of the ultra-hot Jupiter KELT-9,b obtained with the HARPS-N high-resolution spectrograph in the context of the Global Architecture of Planetary Systems (GAPS2) project, to characterise the atmosphere via single-line analysis. We extracted the transmission spectrum of each individual line by comparing the master out-of-transit spectrum with the in-transit spectra and computing the weighted average of the tomography in the planet reference frame. We corrected for the centre-to-limb variation and the Rossiter-McLaughlin effect by modelling the region of the star disc obscured by the planet during the transit and subtracting it from the master-out spectrum. We detected all six observable lines of the Balmer series within the HARPS-N wavelength range, from H$\alpha$ to H$\zeta$, with a significance exceeding 5$\sigma$. We focussed on metal species, detecting Na I, Ca I, Ca II, Fe I, Fe II, Mg I, Ti II, Sc II, and Cr II lines. This is the first detection in the atmosphere of an exoplanet of H$\epsilon$ and H$\zeta$ lines, as well as of individual lines of Sc II and Cr II. Our detections are supported by a comparison with published synthetic transmission spectra of KELT-9b obtained accounting for non-local thermodynamic equilibrium effects. The results underline the presence of a systematic blueshift due to night-side to day-side winds. The single-line analysis allowed us not only to assess the presence of atomic species in the atmosphere of KELT-9 b, but also to further characterise the local stratification of the atmosphere. Coupling the height distribution of the detected species with the velocity shift retrieved, we acknowledged the height distribution of night-side to day-side winds. Moreover, the study of the rotational broadening of different species supports the prediction of a tidally locked planet rotating as a rigid body.

Deploying federated learning (FL) in real-world scenarios, particularly in healthcare, poses challenges in communication and security. In particular, with respect to the federated aggregation procedure, researchers have been focusing on the study of secure aggregation (SA) schemes to provide privacy guarantees over the model's parameters transmitted by the clients. Nevertheless, the practical availability of SA in currently available FL frameworks is currently limited, due to computational and communication bottlenecks. To fill this gap, this study explores the implementation of SA within the open-source Fed-BioMed framework. We implement and compare two SA protocols, Joye-Libert (JL) and Low Overhead Masking (LOM), by providing extensive benchmarks in a panel of healthcare data analysis problems. Our theoretical and experimental evaluations on four datasets demonstrate that SA protocols effectively protect privacy while maintaining task accuracy. Computational overhead during training is less than 1% on a CPU and less than 50% on a GPU for large models, with protection phases taking less than 10 seconds. Incorporating SA into Fed-BioMed impacts task accuracy by no more than 2% compared to non-SA scenarios. Overall this study demonstrates the feasibility of SA in real-world healthcare applications and contributes in reducing the gap towards the adoption of privacy-preserving technologies in sensitive applications., Comment: Accepted at the 5-th MICCAI Workshop on Distributed, Collaborative and Federated Learning in Conjunction with MICCAI 2024

We collected more than 300 high-resolution spectra of the 300 Myr old star BD+40 2790 (TOI-2076) over ~3 years. This star hosts three transiting planets discovered by TESS, with orbital periods ~10, 21, and 35 days. BD+40 2790 shows an activity-induced scatter larger than 30 m/s in the radial velocities. We employed different methods to measure the stellar radial velocities and several models to filter out the dominant stellar activity signal, in order to bring to light the planet-induced signals which are expected to have semi-amplitudes one order of magnitude lower. We evaluated the mass loss rate of the planetary atmospheres using photoionization hydrodynamic modeling. The dynamical analysis confirms that the three sub-Neptune-sized companions (our radius measurements are $R_b$=2.54$\pm$0.04, $R_c$=3.35$\pm$0.05, and $R_d$=3.29$\pm$0.06 $R_{\rm Earth}$) have masses in the planetary regime. We derive 3$\sigma$ upper limits below or close to the mass of Neptune for all the planets: 11--12, 12--13.5, and 14--19 $M_{\rm Earth}$ for planet $b$, $c$, and $d$ respectively. In the case of planet $d$, we found promising clues that the mass could be between ~7 and 8 $M_{\rm Earth}$, with a significance level between 2.3--2.5$\sigma$ (at best). This result must be further investigated using other analysis methods or using high-precision near-IR spectrographs to collect new radial velocities, which could be less affected by stellar activity. Atmospheric photo-evaporation simulations predict that BD+40~2790 b is currently losing its H-He gaseous envelope, which will be completely lost at an age within 0.5--3 Gyr if its current mass is lower than 12 $M_{\rm Earth}$. BD+40 2790 c could have a lower bulk density than $b$, and it could retain its atmosphere up to an age of 5 Gyr. For the outermost planet $d$, we predict almost negligible evolution of its mass and radius induced by photo-evaporation., Comment: Accepted for publication on A&A. Abstract abridged

Consider the family of semilinear parabolic problems \begin{equation*} \left\{ \begin{array}{lll} u_{t}(x,t) = \Delta u(x,t) - au(x,t) + f(u(x,t)), \,\,\, x \in \Omega_{\epsilon}, t > 0, \\ \frac{\partial u}{\partial N} (x,t) = g(u(x,t)), \,\,\, x \in \partial \Omega_{\epsilon}, t > 0, \end{array} \right. \end{equation*} where $a > 0$, $\Omega$ is the unit square, $\Omega_{\epsilon} = h_{\epsilon}(\Omega)$, $h_{\epsilon}$ is a family of $C^{m}$ - diffeomorphisms, $m \geq 1$, which converge to the identity of $\Omega$ in $C^{\alpha}$ norm, if $\alpha <1$ but do not converge in the $C^{1}$ - norm and, $f,g: \mathbb{R} \rightarrow \mathbb{R}$ are real functions. We show that a weak version of this problem, transported to the fixed domain $\Omega$ by a ``pull-back'' procedure, is well posed for $0 <\epsilon \leq \epsilon_{0}$, $\epsilon_{0} > 0$, in a suitable phase space, the associated semigroup has a global attractor $\mathcal{A}_{\epsilon}$ and the family $\{ \mathcal{A}_{\epsilon} \}_{0 \, < \, \epsilon \, \leq \, \epsilon_{0}}$ converges as $\epsilon \to 0$ to the attractor of the limiting problem: \begin{equation*}\ \left\{ \begin{array}{lll} u_{t}(x,t) = \Delta u(x,t) - au(x,t) + f(u(x,t)), \,\,\, x \in \Omega, t > 0, \\ \frac{\partial u}{\partial N} (x,t) = g(u(x,t))\mu, \,\,\, x \in \partial \Omega, t > 0, \end{array} \right. \end{equation*} where $\mu$ is essentially the limit of the Jacobian determinant of the diffeomorphism ${h_{\epsilon}}_{| \partial \Omega} : \partial \Omega \rightarrow \partial h_{\epsilon}(\Omega)$ (but does not depend on the particular family $h_{\epsilon})$.

Fast emitting polymeric scintillators are requested in advanced applications where high-speed detectors with large signal-to-noise ratio are needed. However, their low density implies a weak stopping power of high energy radiations, thus a limited light output and sensitivity. To enhance their performances, polymeric scintillators can be loaded with dense nanoparticles (NPs). We investigate the properties of a series of polymeric scintillators by means of photoluminescence and scintillation spectroscopy, comparing standard scintillators with a composite system loaded with dense hafnium dioxide (HfO2) NPs. The nanocomposite shows a scintillation yield enhancement of +100% with unchanged time response. We provide for the first time an interpretation of this effect, pointing out the local effect of NPs in the generation of emissive states upon interaction with the ionizing radiation. The obtained results indicate that coupling of fast conjugated emitters with optically inert dense NPs could allow to surpass the actual limits of pure polymeric scintillators., Comment: 14 pages, 4 figures

We provide a thermodynamic derivation of the only-phase Popov action functional, which is often adopted to study the low-energy effective hydrodynamics of a generic nonrelativistic superfluid. It is shown that the crucial assumption is the use of the saddle point approximation after neglecting the quantum-pressure term. As an application, we analyze charged superfluid (superconductors) coupled to the electromagnetic field at zero temperature. Our only-phase and minimally-coupled theory predicts the decay of the electrostatic field inside a superconductor with a characteristic length much smaller than the London penetration depth of the static magnetic field. This result is confirmed also by a relativistic only-phase Popov action we obtain from the Klein-Gordon Lagrangian., Comment: 13 pages, 0 figures. Published in Journal of Physics A: Mathematical and Theoretical

The FlyEye design makes its debut in the ESA's NEOSTEL developed by OHB-Italia. This pioneering FlyEye telescope integrates a monolithic 1-meter class primary mirror feeding 16 CCD cameras for discovering Near-Earth Object (NEO) and any class of transient phenomena. OHB-Italia is the prime contractor, receiving extended support from the Italian National Institute for Astrophysics (INAF) in the ESA's NEOSTED program's integration and testing. The FlyEye distinctive design splits the Field of View into 16 channels, creating a unique multi-telescope system with a panoramic 44 square degree Field of View and a seeing-size pixel-scale, enabling NEOs detection down to apparent magnitudes 21.5 insisting on a 1m diameter spherical mirror. The scientific products of a similar FlyEye telescope can complement facilities such as Vera Rubin (former LSST) and ZTF. The FlyEye has the ability to survey two-thirds of the visible sky about three times per night can revolutionize time-domain astronomy, enabling comprehensive studies of transient phenomena, placing FlyEye in a new era of exploration of the dynamic universe. Efforts to develop automated calibration and testing procedures are keys to realizing this transformative potential., Comment: 9 pages, 1 figure, SPIE Astronomical Telescopes + Instrumentation, Ground-based and Airborne Instrumentation for Astronomy X, 16-21 June 2024

Bayesian predictive probabilities are commonly used for interim monitoring of clinical trials through efficacy and futility stopping rules. Despite their usefulness, calculation of predictive probabilities, particularly in pre-experiment trial simulation, can be a significant challenge. We introduce an approximation for computing predictive probabilities using either a p-value or a posterior probability that significantly reduces this burden. We show the approximation has a high degree of concordance with standard Monte Carlo imputation methods for computing predictive probabilities, and present five simulation studies comparing the approximation to the full predictive probability for a range of primary analysis strategies: dichotomous, time-to-event, and ordinal endpoints, as well as historical borrowing and longitudinal modeling. We find that this faster method of predictive probability approximation works well in all five applications, thus significantly reducing the computational burden of trial simulation, allowing more virtual trials to be simulated to achieve greater precision in estimating trial operating characteristics., Comment: under review

In this paper, we consider the linear evolution equation $dy(t)=Ay(t)dt+Gy(t)dx(t)$, where $A$ is a closed operator, associated to a semigroup, with good smoothing effects in a Banach space $E$, $x$ is a nonsmooth path, which is $\eta$-H\"older continuous for some $\eta\in (1/3,1/2]$, and $G$ is a non-smoothing linear operator on $E$. We prove that the Cauchy problem associated with the previous equation admits a unique mild solution and we also show that the solution increases the regularity of the initial datum as soon as time evolves. Then, we show that the mild solution is also an integral solution and this allows us to prove a It\^o formula.

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full story. Grammatical constructions that convey meaning through a particular combination of several morphosyntactic elements -- for example, interrogative sentences with special markers and/or word orders -- are not labeled holistically. We argue for (i) augmenting UD annotations with a 'UCxn' annotation layer for such meaning-bearing grammatical constructions, and (ii) approaching this in a typologically informed way so that morphosyntactic strategies can be compared across languages. As a case study, we consider five construction families in ten languages, identifying instances of each construction in UD treebanks through the use of morphosyntactic patterns. In addition to findings regarding these particular constructions, our study yields important insights on methodology for describing and identifying constructions in language-general and language-particular ways, and lays the foundation for future constructional enrichment of UD treebanks., Comment: LREC-COLING 2024

Evolvability is defined as the ability of a population to generate heritable variation to facilitate its adaptation to new environments or selection pressures. In this article, we consider evolvability as a phenotypic trait subject to evolution and discuss its implications in the adaptation of cell populations. We explore the evolutionary dynamics of an actively proliferating population of cells subject to changes in their proliferative potential and their evolvability using a stochastic individual-based model and its deterministic continuum counterpart through numerical simulations of these models. We find robust adaptive trajectories that rely on cells with high evolvability rapidly exploring the phenotypic landscape and reaching the proliferative potential with the highest fitness. The strength of selection on the proliferative potential, and the cost associated with evolvability, can alter these trajectories such that, if both are sufficiently constraining, highly evolvable populations can become extinct in our individual-based model simulations. We explore the impact of this interaction at various scales, discussing its effects in undisturbed environments and also in disrupted contexts, such as cancer., Comment: 26 pages, 6 figures, 1 table

A fundamental feature of collective cell migration is phenotypic heterogeneity which, for example, influences tumour progression and relapse. While current mathematical models often consider discrete phenotypic structuring of the cell population, in-line with the `go-or-grow' hypothesis \cite{hatzikirou2012go, stepien2018traveling}, they regularly overlook the role that the environment may play in determining the cells' phenotype during migration. Comparing a previously studied volume-filling model for a homogeneous population of generalist cells that can proliferate, move and degrade extracellular matrix (ECM) \cite{crossley2023travelling} to a novel model for a heterogeneous population comprising two distinct sub-populations of specialist cells that can either move and degrade ECM or proliferate, this study explores how different hypothetical phenotypic switching mechanisms affect the speed and structure of the invading cell populations. Through a continuum model derived from its individual-based counterpart, insights into the influence of the ECM and the impact of phenotypic switching on migrating cell populations emerge. Notably, specialist cell populations that cannot switch phenotype show reduced invasiveness compared to generalist cell populations, while implementing different forms of switching significantly alters the structure of migrating cell fronts. This key result suggests that the structure of an invading cell population could be used to infer the underlying mechanisms governing phenotypic switching., Comment: 35 pages, 12 figures

In this paper we consider the vector-valued Schr\"{o}dinger operator $-\Delta + V$, where the potential term $V$ is a matrix-valued function whose entries belong to $L^1_{\rm loc}(\mathbb{R}^d)$ and, for every $x\in\mathbb{R}^d$, $V(x)$ is a symmetric and nonnegative definite matrix, with non positive off-diagonal terms and with eigenvalues comparable each other. For this class of potential terms we obtain maximal inequality in $L^1(\mathbb{R}^d,\mathbb{R}^m).$ Assuming further that the minimal eigenvalue of $V$ belongs to some reverse H\"older class of order $q\in(1,\infty)\cup\{\infty\}$, we obtain maximal inequality in $L^p(\mathbb{R}^d,\mathbb{R}^m)$, for $p$ in between $1$ and some $q$.

In this paper, we study the stability of traveling wave solutions arising from a credit rating migration problem with a free boundary, After some transformations, we turn the Free Boundary Problem into a fully nonlinear parabolic problem on a fixed domain and establish a rigorous stability analysis of the equilibrium in an exponentially weighted function space. It implies the convergence of the discounted value of bonds that stands as an attenuated traveling wave solution.

The intrinsic variability due to the magnetic activity of young active stars is one of the main challenges in detecting and characterising exoplanets. We present a method able to model the stellar photosphere and its surface inhomogeneities (starspots) in young/active and fast-rotating stars, based on the cross-correlation function (CCF) technique, to extract information about the spot configuration of the star. Within the Global Architecture of Planetary Systems (GAPS) Project at the Telescopio Nazionale Galileo, we analysed more than 300 spectra of the young planet-hosting star V1298 Tau provided by HARPS-N high-resolution spectrograph. By applying the SpotCCF model to the CCFs we extracted the spot configuration (latitude, longitude and projected filling factor) of this star, and also provided the new RVs time series of this target. We find that the features identified in the CCF profiles of V1298 Tau are modulated by the stellar rotation, supporting our assumption that they are caused by starspots. The analysis suggests a differential rotation velocity of the star with lower rotation at higher latitudes. Also, we find that SpotCCF provides an improvement in RVs extraction with a significantly lower dispersion with respect to the commonly used pipelines, with consequent mitigation of the stellar activity contribution modulated with stellar rotation. A detection sensitivity test, by the direct injection of a planetary signal into the data, confirmed that the SpotCCF model improves the sensitivity and ability to recover planetary signals. Our method enables the modelling of the stellar photosphere, extracting the spot configuration of young/active and rapidly rotating stars. It also allows for the extraction of optimised RV time series, thereby enhancing our detection capabilities for new exoplanets and advancing our understanding of stellar activity., Comment: 18 pages, 20 figures, accepted by A&A

Context. Different theories have been developed to explain the origins and properties of close-in giant planets, but none of them alone can explain all of the properties of the warm Jupiters (WJs, Porb = 10 - 200 days). One of the most intriguing characteristics of WJs is that they have a wide range of orbital eccentricities, challenging our understanding of their formation and evolution. Aims. The investigation of these systems is crucial in order to put constraints on formation and evolution theories. TESS is providing a significant sample of transiting WJs around stars bright enough to allow spectroscopic follow-up studies. Methods. We carried out a radial velocity (RV) follow-up study of the TESS candidate TOI-4515 b with the high-resolution spectrograph HARPS-N in the context of the GAPS project, the aim of which is to characterize young giant planets, and the TRES and FEROS spectrographs. We then performed a joint analysis of the HARPS-N, TRES, FEROS, and TESS data in order to fully characterize this planetary system. Results. We find that TOI-4515 b orbits a 1.2 Gyr-old G-star, has an orbital period of Pb = 15.266446 +- 0.000013 days, a mass of Mb = 2.01 +- 0.05 MJ, and a radius of Rb = 1.09 +- 0.04 RJ. We also find an eccentricity of e = 0.46 +- 0.01, placing this planet among the WJs with highly eccentric orbits. As no additional companion has been detected, this high eccentricity might be the consequence of past violent scattering events., Comment: 20 pages, 16 figures

We consider systems of elliptic equations, possibly coupled up to the second-order, on the L^p(R^d;C^m)-scale. Under suitable assumptions we prove that the minimal realization in L^p(R^d;C^m)$ generates a strongly continuous analytic semigroup. We also prove the consistency of the semigroup on the L^p-scale and some spectral results.

We formulate haptotaxis models of cancer invasion wherein the infiltrating cancer cells can occupy a spectrum of states in phenotype space, ranging from `fully mesenchymal' to `fully epithelial'. The more mesenchymal cells are those that display stronger haptotaxis responses and have greater capacity to modify the extracellular matrix (ECM) through enhanced secretion of matrix-degrading enzymes (MDEs). However, as a trade-off, they have lower proliferative capacity than the more epithelial cells. The framework is multiscale in that we start with an individual-based model that tracks the dynamics of single cells, which is based on a branching random walk over a lattice representing both physical and phenotype space. We formally derive the corresponding continuum model, which takes the form of a coupled system comprising a partial integro-differential equation for the local cell population density function, a partial differential equation for the MDE concentration and an infinite-dimensional ordinary differential equation for the ECM density. Despite the intricacy of the model, we show, through formal asymptotic techniques, that for certain parameter regimes it is possible to carry out a detailed travelling wave analysis and obtain invading fronts with spatial structuring of phenotypes. Precisely, the most mesenchymal cells dominate the leading edge of the invasion wave and the most epithelial (and most proliferative) dominate the rear, representing a bulk tumour population. As such, the model recapitulates similar observations into a front to back structuring of invasion waves into leader-type and follower-type cells, witnessed in an increasing number of experimental studies over recent years.

Short-period giant planets are frequently found to be solitary compared to other classes of exoplanets. Small inner companions to giant planets with $P \lesssim$ 15 days are known only in five compact systems: WASP-47, Kepler-730, WASP-132, TOI-1130, and TOI-2000. Here, we report the confirmation of TOI-5398, the youngest compact multi-planet system composed of a hot sub-Neptune (TOI-5398 c, $P_{\rm c}$ = 4.77271 days) orbiting interior to a short-period Saturn (TOI-5398 b, $P_{\rm b}$ = 10.590547 days) planet, both transiting around a 650 $\pm$ 150 Myr G-type star. As part of the GAPS Young Object project, we confirmed and characterised this compact system, measuring the radius and mass of both planets, thus constraining their bulk composition. Using multidimensional Gaussian processes, we simultaneously modelled stellar activity and planetary signals from TESS Sector 48 light curve and our HARPS-N radial velocity time series. We have confirmed the planetary nature of both planets, TOI-5398 b and TOI-5398 c, alongside a precise estimation of stellar parameters. Through the use of astrometric, photometric, and spectroscopic observations, our findings indicate that TOI-5398 is a young, active G dwarf star (650 $\pm$ 150 Myr), with a rotational period of $P_{\rm rot}$ = 7.34 days. The transit photometry and radial velocity measurements enabled us to measure both the radius and mass of planets b, $R_b = 10.30\pm0.40 R_{\oplus}$, $M_b = 58.7\pm5.7 M_{\oplus}$, and c, $R_c = 3.52 \pm 0.19 R_{\oplus}$, $M_c = 11.8\pm4.8 M_{\oplus}$. TESS observed TOI-5398 during sector 48 and no further observations are planned in the current Extended Mission, making our ground-based light curves crucial for ephemeris improvement. With a Transmission Spectroscopy Metric value of around 300, TOI-5398 b is the most amenable warm giant (10 < $P$ < 100 days) for JWST atmospheric characterisation., Comment: 29 pages, Paper accepted for publication in Astronomy & Astrophysics

We present the characterisation of the two transiting planets around HD 152843 (TOI 2319, TIC 349488688) using an intensive campaign of HARPS-N radial velocities, and two sectors of TESS data. These data reveal a unique and fascinating system: HD 152843 b and c have near equal masses of around 9 M$_\oplus$ but differing radii of $3.05 \pm 0.11$ R$_\oplus$ and $5.94^{+0.18}_{-0.16}$ R$_\oplus$ , respectively, and orbital periods of $11.62071^{+9.6e-05}_{-0.000106}$ days and $19.502104^{+7.4e-05}_{-8.5e-05}$ days. This indicates that HD 152843 c is in the lowest fifth percentile in density of the known exoplanet population, and has the longest orbital period among these low density planets. Further, HD 152843 c's radius places it in the Saturn valley, the observed lack of planets larger than Neptune, but smaller than Saturn. The orbital periods of these planets indicate they are near a 5:3 mean motion resonance, indicating the possibility of transit timing variations, and hints at the possibility of interaction with a third planet at some point in the evolution of this system. Further, the brightness of the host star and the low density of HD 152843 c make it a key target for atmospheric characterisation., Comment: Submitted for review to the Monthly Notices of the Royal Astronomical Society. 13 pages, 16 figures

We report systematic numerical simulations of the collision of a bright matter-wave soliton made of Bose-condensed alkali-metal atoms through a narrow potential barrier by using the three-dimensional Gross-Pitaevskii equation. In this way, we determine how the transmission coefficient depends on the soliton impact velocity and the barrier height. Quite remarkably, we also obtain the regions of parameters where there is the collapse of the bright soliton induced by the collision. We compare these three-dimensional results with the ones obtained by three different one-dimensional nonlinear Schr\"odinger equations. We find that a specifically modified nonpolynomial Schr\"odinger equation is able to accurately assess the transmission coefficient even in a region in which the usual nonpolynomial Schr\"odinger equation does collapse. In particular, this simplified but very effective one-dimensional model takes into account the transverse width dynamics of the soliton with an ordinary differential equation coupled to the partial differential equation of the axial wave function of the Bose-Einstein condensate., Comment: 9 pages, 6 figures. Submitted for publication in Scientific Reports. Numerical package available at https://github.com/lorenzifrancesco/SolitonDynamics.jl

Healthcare data is often split into medium/small-sized collections across multiple hospitals and access to it is encumbered by privacy regulations. This brings difficulties to use them for the development of machine learning and deep learning models, which are known to be data-hungry. One way to overcome this limitation is to use collaborative learning (CL) methods, which allow hospitals to work collaboratively to solve a task, without the need to explicitly share local data. In this paper, we address a prostate segmentation problem from MRI in a collaborative scenario by comparing two different approaches: federated learning (FL) and consensus-based methods (CBM). To the best of our knowledge, this is the first work in which CBM, such as label fusion techniques, are used to solve a problem of collaborative learning. In this setting, CBM combine predictions from locally trained models to obtain a federated strong learner with ideally improved robustness and predictive variance properties. Our experiments show that, in the considered practical scenario, CBMs provide equal or better results than FL, while being highly cost-effective. Our results demonstrate that the consensus paradigm may represent a valid alternative to FL for typical training tasks in medical imaging.

Time-of-Flight Positron Emission Tomography is a medical imaging technique, based on the detection of two back-to-back {\gamma}-photons generated from radiotracers injected in the body. Its limit is the ability of employed scintillation detectors to discriminate in time the arrival of {\gamma}-pairs, i.e. the coincidence time resolution (CTR). A CTR < 50 ps that would enable fast imaging with ultralow radiotracer dose. Monolithic materials do not have simultaneously the required high light output and fast emission characteristics, thus the concept of scintillating heterostructure is proposed, where the device is made of a dense scintillator coupled to a fast-emitting light material. Here we present a composite polymeric scintillator, whose density has been increased upon addition of hafnium oxide nanoparticles. This enhanced by +300% its scintillation yield, surpassing commercial plastic scintillators. The nanocomposite is coupled to bismuth germanate oxide (BGO) realizing a multilayer scintillator. We observed the energy sharing between its components, which activate the nanocomposite fast emission enabling a net CTR improvement of 25% with respect to monolithic BGO. These results demonstrate that a controlled loading with dense nanomaterials is an excellent strategy to enhance the performance of polymeric scintillators for their use in advanced radiation detection and imaging technologies.

A major challenge in imaging genetics and similar fields is to link high-dimensional data in one domain, e.g., genetic data, to high dimensional data in a second domain, e.g., brain imaging data. The standard approach in the area are mass univariate analyses across genetic factors and imaging phenotypes. That entails executing one genome-wide association study (GWAS) for each pre-defined imaging measure. Although this approach has been tremendously successful, one shortcoming is that phenotypes must be pre-defined. Consequently, effects that are not confined to pre-selected regions of interest or that reflect larger brain-wide patterns can easily be missed. In this work we introduce a Partial Least Squares (PLS)-based framework, which we term Cluster-Bootstrap PLS (CLUB-PLS), that can work with large input dimensions in both domains as well as with large sample sizes. One key factor of the framework is to use cluster bootstrap to provide robust statistics for single input features in both domains. We applied CLUB-PLS to investigating the genetic basis of surface area and cortical thickness in a sample of 33,000 subjects from the UK Biobank. We found 107 genome-wide significant locus-phenotype pairs that are linked to 386 different genes. We found that a vast majority of these loci could be technically validated at a high rate: using classic GWAS or Genome-Wide Inferred Statistics (GWIS) we found that 85 locus-phenotype pairs exceeded the genome-wide suggestive (P<1e-05) threshold., Comment: 12 pages, 4 Figures, 2 Tables

The Rocky Planet Search (RPS) program is dedicated to a blind radial velocity (RV) search of planets around bright stars in the Northern hemisphere, using the high-resolution echelle spectrograph HARPS-N installed on the Telescopio Nazionale Galileo (TNG). The goal of this work is to revise and update the properties of three planetary systems by analysing the HARPS-N data with state-of-the-art stellar activity mitigation tools. The stars considered are HD 99492 (83Leo B), HD 147379 (Gl617 A) and HD 190007. We employ a systematic process of data modelling, that we selected from the comparison of different approaches. We use YARARA to remove instrumental systematics from the RV, and then use SPLEAF to further mitigate the stellar noise with a multidimensional correlated noise model. We also search for transit features in the Transiting Exoplanets Survey Satellite (TESS) data of these stars. We report on the discovery of a new planet around HD 99492, namely HD 99492 c, with an orbital period of 95.2 days and a minimum mass of msin i = 17.9 M_Earth, and refine the parameters of HD 99492 b. We also update and refine the Keplerian solutions for the planets around HD 147379 and HD 190007, but do not detect additional planetary signals. We discard the transiting geometry for the planets, but stress that TESS did not exhaustively cover all the orbital phases. The addition of the HARPS-N data, and the use of advanced data analysis tools, has allowed us to present a more precise view of these three planetary systems. It demonstrates once again the importance of long observational efforts such as the RPS program. Added to the RV exoplanet sample, these planets populate two apparently distinct populations revealed by a bimodality in the planets minimum mass distribution. The separation is located between 30 and 50 M_Earth., Comment: 27 pages, 26 figures (13 in Appendix); Accepted for publication in A&A

In recent in vitro experiments on co-culture between breast tumour spheroids and activated immune cells, it was observed that the introduction of the stress hormone cortisol resulted in a decreased immune cell infiltration into the spheroids. Moreover, the presence of cortisol deregulated the normal levels of the pro- and anti-inflammatory cytokines IFN-{\gamma} and IL-10. We present an individual-based model to explore the interaction dynamics between tumour and immune cells under psychological stress conditions. With our model, we explore the processes underlying the emergence of different levels of immune infiltration, with particular focus on the biological mechanisms regulated by IFN-{\gamma} and IL-10. The set-up of numerical simulations is defined to mimic the scenarios considered in the experimental study. Similarly to the experimental quantitative analysis, we compute a score that quantifies the level of immune cell infiltration into the tumour. The results of numerical simulations indicate that the motility of immune cells, their capability to infiltrate through tumour cells, their growth rate and the interplay between these cell parameters can affect the level of immune cell infiltration in different ways. Ultimately, numerical simulations of this model support a deeper understanding of the impact of biological stress-induced mechanisms on immune infiltration.

We develop a new structured compartmental model for the coevolutionary dynamics between susceptible and infectious individuals in heterogeneous SI epidemiological systems. In this model, the susceptible compartment is structured by a continuous variable that represents the level of resistance to infection of susceptible individuals, while the infectious compartment is structured by a continuous variable that represents the viral load of infectious individuals. We first formulate an individual-based model wherein the dynamics of single individuals is described through stochastic processes, which permits a fine-grain representation of individual dynamics and captures stochastic variability in evolutionary trajectories amongst individuals. Next we formally derive the mesoscopic counterpart of this model, which consists of a system of coupled integro-differential equations for the population density functions of susceptible and infectious individuals. Then we consider an appropriately rescaled version of this system and we carry out formal asymptotic analysis to derive the corresponding macroscopic model, which comprises a system of coupled ordinary differential equations for the proportions of susceptible and infectious individuals, the mean level of resistance to infection of susceptible individuals, and the mean viral load of infectious individuals. Overall, this leads to a coherent mathematical representation of the coevolutionary dynamics between susceptible and infectious individuals across scales. We provide well-posedness results for the mesoscopic and macroscopic models, and we show that there is excellent agreement between analytical results on the long-time behaviour of the components of the solution to the macroscopic model, the results of Monte Carlo simulations of the individual-based model, and numerical solutions of the macroscopic model.

We present the results of a high-cadence and high-precision radial velocity (RV) monitoring of 3 late-type dwarf stars hosting long-period giants with well-measured orbits, in order to search for short-period sub-Neptunes (SN, $M \sin i < 30$ M$_\oplus$). Building on the results and expertise of our previous studies, we carry out combined fits of our HARPS-N data with literature RVs, using MCMC analyses and Gaussian Process regression. We then use the results of our survey to estimate the frequency of sub-Neptunes in systems hosting cold-Jupiters, $f(SN|CJ)$, and compare it with the frequency around field M-dwarfs, $f(SN)$. We identify a new short-period low-mass planet orbiting GJ 328, GJ 328\,c, with $P_c = 241.8^{+1.3}_{-1.7}$ d and $M_c \sin i = 21.4^{+ 3.4}_{- 3.2}$ M$_\oplus$. We moreover identify and model the chromospheric activity signals and rotation periods of GJ 649 and GJ 849, around which no additional planet is found. Then, taking into account also planetary system around the previosuly-analyzed low-mass star BD-11 4672, we derive an estimate of the frequencies of inner planets in such systems. In particular $f(SN|CJ) = 0.25^{+0.58}_{-0.07}$ for mini-Neptunes ($10$ M$_\oplus < M \sin i < 30$ M$_\oplus$, $P < 150$ d), marginally larger than $f(SN)$. For lower-mass planets ($M \sin i < 10$ M$_\oplus$) instead $f(SN|CJ) <0.69$, compatible with $f(SN)$. In light of the newly detected mini-Neptune, we find tentative evidence of a positive correlation between the presence of those planets and that of inner low-mass planets, $f(SN|CJ) > f(SN)$. This might indicate that cold Jupiters have an opposite influence in the formation of inner sub-Neptunes around late-type dwarfs as opposed to their solar-type counterparts, boosting the formation of mini-Neptunes instead of impeding it., Comment: 21 pages, 17 figures, 8 table. Accepted by A&A

The study of loss function distributions is critical to characterize a model's behaviour on a given machine learning problem. For example, while the quality of a model is commonly determined by the average loss assessed on a testing set, this quantity does not reflect the existence of the true mean of the loss distribution. Indeed, the finiteness of the statistical moments of the loss distribution is related to the thickness of its tails, which are generally unknown. Since typical cross-validation schemes determine a family of testing loss distributions conditioned on the training samples, the total loss distribution must be recovered by marginalizing over the space of training sets. As we show in this work, the finiteness of the sampling procedure negatively affects the reliability and efficiency of classical tail estimation methods from the Extreme Value Theory, such as the Peaks-Over-Threshold approach. In this work we tackle this issue by developing a novel general theory for estimating the tails of marginal distributions, when there exists a large variability between locations of the individual conditional distributions underlying the marginal. To this end, we demonstrate that under some regularity conditions, the shape parameter of the marginal distribution is the maximum tail shape parameter of the family of conditional distributions. We term this estimation approach as Cross Tail Estimation (CTE). We test cross-tail estimation in a series of experiments on simulated and real data, showing the improved robustness and quality of tail estimation as compared to classical approaches, and providing evidence for the relationship between overfitting and loss distribution tail thickness.

While the neural ODE formulation of normalizing flows such as in FFJORD enables us to calculate the determinants of free form Jacobians in O(D) time, the flexibility of the transformation underlying neural ODEs has been shown to be suboptimal. In this paper, we present AFFJORD, a neural ODE-based normalizing flow which enhances the representation power of FFJORD by defining the neural ODE through special augmented transformation dynamics which preserve the topology of the space. Furthermore, we derive the Jacobian determinant of the general augmented form by generalizing the chain rule in the continuous sense into the Cable Rule, which expresses the forward sensitivity of ODEs with respect to their initial conditions. The cable rule gives an explicit expression for the Jacobian of a neural ODE transformation, and provides an elegant proof of the instantaneous change of variable. Our experimental results on density estimation in synthetic and high dimensional data, such as MNIST, CIFAR-10 and CelebA 32x32, show that AFFJORD outperforms the baseline FFJORD through the improved flexibility of the underlying vector field.

In Diffusion Probabilistic Models (DPMs), the task of modeling the score evolution via a single time-dependent neural network necessitates extended training periods and may potentially impede modeling flexibility and capacity. To counteract these challenges, we propose leveraging the independence of learning tasks at different time points inherent to DPMs. More specifically, we partition the learning task by utilizing independent networks, each dedicated to learning the evolution of scores within a specific time sub-interval. Further, inspired by residual flows, we extend this strategy to its logical conclusion by employing separate networks to independently model the score at each individual time point. As empirically demonstrated on synthetic and image datasets, our approach not only significantly accelerates the training process by introducing an additional layer of parallelization atop data parallelization, but it also enhances density estimation performance when compared to the conventional training methodology for DPMs.

We investigate the role of quantum fluctuations in the dynamics of a bosonic Josephson junction in $D$ spatial dimensions, by using beyond mean-field Gaussian corrections. We derive some key dynamical properties in a systematic way for $D=3, 2, 1$. In particular, we compute the Josephson frequency in the regime of low population imbalance. We also obtain the critical strength of the macroscopic quantum self-trapping. Our results show that quantum corrections increase the Josephson frequency in spatial dimensions $D=2$ and $D=3$, but they decrease it in the $D=1$ case. The critical strength of macroscopic quantum self-trapping is instead reduced by quantum fluctuations in $D=2$ and $D=3$ cases, while it is enhanced in the $D=1$ configuration. We show that the difference between the cases of D = 2 and D = 3 on one side, and D = 1 on the other, can be related to the qualitatively different dependence of the interaction strength on the scattering length in the different dimensions., Comment: 25 pages, 9 figures, 2 tables