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Transferred plasma catheter for endotherapeutic applications: a parametric study of guided streamers dynamics
No full textInternational audienceNon-thermal atmospheric pressure plasma jets (APPJs) are increasingly used in biomedical applications due to their low temperatures and ability to generate reactive oxygen and nitrogen species (RONS), making them suitable for sensitive environments like medical therapies. The transferred plasma catheter (TPC), a variant of APPJ, shows promise for endoscopic applications but requires precise control of plasma dynamics in confined spaces to ensure safety and efficacy. Despite extensive studies on guided streamers in traditional APPJs, there is limited understanding of streamer behavior in TPC configurations, particularly in challenging scenarios involving grounded metallic surfaces. This study examines the spatiotemporal dynamics of guided streamers generated by TPCs under varying gap distances to establish a robust framework for safe and effective plasma delivery in endoscopic settings. Combining electrical and optical diagnostics, the study characterizes streamer propagation, electric field profiles, and plasma-induced currents in a helium-driven TPC delivering cold plasma to a grounded metal target across gaps of 2 to 18 mm. Results show that streamers maintain charge stability and effectively interact with the target for gap distances below 12 mm, producing significant therapeutic currents. Beyond this threshold, propagation deteriorates due to recombination and reduced electric field intensity. For shorter gaps, counterpropagating waves and secondary streamer interactions are observed, while larger gaps lead to charge dissipation and reduced efficacy. These findings highlight the importance of optimizing gap distances for plasma-assisted endoscopic procedures and demonstrate the TPC's robustness in adverse conditions
A non-compensated Clark–Ocone formula for functionals of counting processes
No full textInternational audienceIn this paper, we develop a representation formula of Clark–Ocone type for any integrable Poisson functionals, which extends the Poisson imbedding for point processes. This representation formula differs from the classical Clark–Ocone formula on three accounts. First the representation holds with respect to the Poisson measure instead of the compensated one; second the representation holds true in L1 and not in L2; and finally contrary to the classical Clark–Ocone formula the integrand is defined as a pathwise operator and not as a L2-limiting object. We make use of Malliavin’s calculus and of a decomposition with uncompensated iterated integrals derived in [Hillairet and Réveillac, Electron. J. Probab. 29 (2024) 1–33] to establish this non-compensated Clark–Ocone representation formula and to characterize the integrand, which turns out to be a predictable integrable process
The H.E.S.S. extragalactic sky survey with the first decade of observations
No full textInternational audienceThe results of the first extragalactic gamma-ray survey by the High Energy Stereoscopic System (H.E.S.S.) are presented. The survey comprises 2720 hours of very high-energy gamma-ray observations of the extragalactic sky, recorded with H.E.S.S. from 2004 up to the end of 2012. These data have been re-analysed using a common consistent set of up-to-date data calibration and analysis tools. From this analysis, a list of 23 detected objects, predominantly blazars, was obtained. This catalogue was assessed in terms of the source class populations that it contains. The level of source parameter bias for the blazar sources, probed by this observational dataset, was evaluated using Monte-Carlo simulations. Spectral results obtained with the H.E.S.S. data were compared with the Fermi-LAT catalogues to present the full gamma-ray picture of the detected objects. Lastly, this unique dataset was used to assess the contribution of BL Lacertae objects and flat-spectrum radio quasars to the extragalactic gamma-ray background light at several hundreds of gigaelectronvolts. These results are accompanied by the release of the high-level data to the astrophysical community
Two-dimensional infrared spectroscopy using a fast-scanning interferometer and chirped pulse up-conversion at 100 kHz
No full textInternational audienceWe report on a 100-kHz two-dimensional infrared (2DIR) spectrometer in the pump-probe geometry, which we apply to the measurement of the 2DIR spectrum of carboxy-hemoglobin. The probe pulses are spectrally resolved by chirped-pulse upconversion (CPU) using a fast 2048-pixel linescan CMOS camera. The two-pulse pump sequence is generated using a conventional interferometer with a fast-scanning mechanical delay line allowing to achieve a scanning frequency of 2 Hz. The resulting modulation frequency of 3.1 kHz is large enough to shift the relevant signal away from the low-frequency noise of the laser source. The combined use of an interferometer on the pump side and of CPU on the probe side opens the way to an improved spectral resolution in both pump and probe dimensions, as compared to currently-available 100-kHz 2DIR spectrometers based on pulse shapers and Mercury-Cadmium Telluride (MCT) detector arrays
Structural and Practical Identifiability of Phenomenological Growth Models for Epidemic Forecasting
No full text29 pages, 6 figuresInternational audiencePhenomenological models are highly effective tools for forecasting disease dynamics using real world data, particularly in scenarios where detailed knowledge of disease mechanisms is limited. However, their reliability depends on the model parameters' structural and practical identifiability. In this study, we systematically analyze the identifiability of six commonly used growth models in epidemiology: the generalized growth model (GGM), the generalized logistic model (GLM), the Richards model, the generalized Richards model (GRM), the Gompertz model, and a modified SEIR model with inhomogeneous mixing. To address challenges posed by non integer power exponents in these models, we reformulate them by introducing additional state variables. This enables rigorous structural identifiability analysis using the StructuralIdentifiability.jl package in JULIA. We validate the structural identifiability results by performing parameter estimation and forecasting using the GrowthPredict MATLAB toolbox. This toolbox is designed to fit and forecast time series trajectories based on phenomenological growth models. We applied it to three epidemiological datasets: weekly incidence data for monkeypox, COVID 19, and Ebola. Additionally, we assess practical identifiability through Monte Carlo simulations to evaluate parameter estimation robustness under varying levels of observational noise. Our results demonstrate the structural and practical identifiability of the models, emphasizing how noise affects parameter estimation accuracy. These findings provide valuable insights into the utility and limitations of phenomenological models for epidemic data analysis, highlighting their adaptability to real world challenges and their role in guiding public health decision making
New Principles For Stabilization Policy
No full textIn a broad class of discrete-time rational-expectations models, I consider stabilization-policy rules making the policy instrument react with coefficient φ ∈ R to a (past, current, or expected future) variable at horizon h ∈ Z, possibly among other variables, possibly with inertia. Using two complex-analysis theorems, I establish analytically some simple, easily interpretable, necessary or sufficient conditions on φ and h for these rules to ensure local-equilibrium determinacy. These conditions lead to new, general principles for stabilization policy in terms of whether, and how strongly or weakly, to react to any variable, at any horizon, in any model, with any policy instrument. Building on these conditions, I characterize the scope of validity of (a generalized version of ) the long-run Taylor principle as a condition for determinacy. I apply all these results to standard interest-rate rules in 134 quantitative monetary-policy models, and find the new principles to be (either typically or occasionally) quantitatively relevant
A stochastic algorithm for deterministic multistage optimization problems
No full textInternational audienceSeveral attempt to dampen the curse of dimensionnality problem of the Dynamic Programming approach for solving multistage optimization problems have been investigated. One popular way to address this issue is the Stochastic Dual Dynamic Programming method (SDDP) introduced by Perreira and Pinto in 1991 for Markov Decision Processes.Assuming that the value function is convex (for a minimization problem), one builds a non-decreasing sequence of lower (or outer) convex approximations of the value function. Those convex approximations are constructed as a supremum of affine cuts. On continuous time deterministic optimal control problems, assuming that the value function is semiconvex, Zheng Qu, inspired by the work of McEneaney, introduced in 2013 a stochastic max-plus scheme that builds upper (or inner) non-increasing approximations of the value function. In this note, we build a common framework for both the SDDP and a discrete time version of Zheng Qu's algorithm to solve deterministic multistage optimization problems. Our algorithm generates monotone approximations of the value functions as a pointwise supremum, or infimum, of basic (affine or quadratic for example) functions which are randomly selected. We give sufficient conditions on the way basic functions are selected in order to ensure almost sure convergence of the approximations to the value function on a set of interest
Fredholm Approach to Nonlinear Propagator Models
No full textWe formulate and solve an optimal trading problem with alpha signals, where transactions induce a nonlinear transient price impact described by a general propagator model, including power-law decay. Using a variational approach, we demonstrate that the optimal trading strategy satisfies a nonlinear stochastic Fredholm equation with both forward and backward coefficients. We prove the existence and uniqueness of the solution under a monotonicity condition reflecting the nonlinearity of the price impact. Moreover, we derive an existence result for the optimal strategy beyond this condition when the underlying probability space is countable. In addition, we introduce a novel iterative scheme and establish its convergence to the optimal trading strategy. Finally, we provide a numerical implementation of the scheme that illustrates its convergence, stability, and the effects of concavity on optimal execution strategies under exponential and power-law decay
Narrowing the Gap between Adversarial and Stochastic MDPs via Policy Optimization
No full textInternational audienceWe consider the problem of learning in adversarial Markov decision processes [MDPs] with an oblivious adversary in a full-information setting. The agent interacts with an environment during episodes, each of which consists of stages, and each episode is evaluated with respect to a reward function that will be revealed only at the end of the episode. We propose an algorithm, called APO-MVP, that achieves a regret bound of order , where and are sizes of the state and action spaces, respectively. This result improves upon the best-known regret bound by a factor of , bridging the gap between adversarial and stochastic MDPs, and matching the minimax lower bound as far as the dependencies in are concerned. The proposed algorithm and analysis completely avoid the typical tool given by occupancy measures; instead, it performs policy optimization based only on dynamic programming and on a black-box online linear optimization strategy run over estimated advantage functions, making it easy to implement. The analysis leverages two recent techniques: policy optimization based on online linear optimization strategies (Jonckheere et al., 2023) and a refined martingale analysis of the impact on values of estimating transitions kernels (Zhang et al., 2023)
Angular analysis of decays
No full textInternational audienceAn angular analysis of decays is presented using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of 9 fb. The analysis is performed in the region of the dilepton invariant mass squared of 1.1-6.0 GeV. In addition, a test of lepton flavour universality is performed by comparing the obtained angular observables with those measured in decays. In general, the angular observables are found to be consistent with the Standard Model expectations as well as with global analyses of other processes, where is either a muon or an electron. No sign of lepton-flavour-violating effects is observed