École Polytechnique

The explosive growth of the Internet of Things (IoT) has driven the development of specialized communication technologies to meet diverse traffic requirements. Narrowband IoT (NB-IoT) is a promising low-power wide-area network (LPWAN) technology designed to support massive machine-type communication (MTC) with delay-tolerant transmission. However, MTC also presents new challenges for NB-IoT, particularly in meeting stringent low-latency and high-reliability requirements. It is therefore important to identify scheduling and resource allocation techniques that enable low-latency applications to achieve their goals. To address these challenges, this paper employs realistic simulations across a variety of traffic scenarios, focusing on uplink scheduling and resource allocation management. We (1) analyze the components contributing to the Quality of Service (QoS) for NB-IoT devices, (2) evaluate the performance of prioritized scheduling schemes and resource unit (RU) configurations for uplink transmission modes, and highlight potential improvements to reduce latency for delay-sensitive traffic, and (3) propose and evaluate a novel hybrid scheduling solution called the Gap-Aware Hybrid Scheduling (GAHUS) algorithm. Our approach enhances network efficiency by prioritizing delay-sensitive traffic to meet QoS requirements. Through simulations, comparisons, and performance evaluations, we demonstrate the effectiveness of GAHUS in exploiting free resource gaps created during long uplink transmissions. The results show that GAHUS supports massive MTC traffic while ensuring reliable performance for delay-sensitive traffic by minimizing rejections and delays.

The Carrollian fluid equations arise from the equations for relativistic fluids in the limit as the speed of light vanishes, and have recently experienced a surge of interest in the theoretical physics community in the context of asymptotic symmetries and flat‐space holography. In this paper, we initiate the rigorous systematic analysis of these equations by studying them in one space dimension in the C1$C^1$ setting. We begin by proposing a notion of isentropic Carrollian equations, and use this to reduce the Carrollian equations to a 2×2$2 \times 2$ system of conservation laws. Using the scheme of Lax, we then classify when C1$C^1$ solutions to the isentropic Carrollian equations exist globally, or blow up in finite time. Our analysis assumes a Carrollian analogue of a constitutive relation for the Carrollian energy density, with exponent in the range γ∈(1,3]$\gamma \in (1, 3]$.

Joseph-Achille Le Bel (b 1847), co-discovered the asymmetric carbon atom, virtually simultaneously with Jacobus H. van’t Hoff in 1874, both working in the laboratory of Adolphe Wurtz in Paris. Until just before his death, he was never elected to the French Academy of Sciences, due in part to the opposition of Marcellin Berthelot. This chapter outlines the lineage of the extremely wealthy Le Bel family, granted exclusive dealership throughout the Alsace of the Pechelbronn mined oil products. It focuses specifically on the influence of his uncle by marriage, Jean-Baptiste Boussingault, himself a distinguished chemist, on the young Joseph-Achille. His precocious intellect was discovered early, including his unusual mathematical aptitude, nurtured in the demanding Alsatian education system which facilitated his entry at seventeen into the École Polytechnique. Although expected by his family to manage the company, his father’s death in 1867 offered enough flexibility to pursue a career in chemistry. Le Bel did not participate in the Franco-Prussian War of 1870 since he had resigned his commission as a polytechnicien cadet upon graduation in 1867. In 1869, Le Bel joined the research laboratory of the distinguished chemist Adolphe Wurtz, at the Medical School in Paris. Wurtz was renowned for training a generation of distinguished chemists from many countries. Even in Wurtz’s laboratory, Le Bel kept faith with his deceased father’s dictate and published some research on petroleum. Le Bel worked in Wurtz’s laboratory through 1884, the year Wurtz died. He lost considerable research productivity due to the Franco-Prussian War of 1870 and its aftermath. Van’t Hoff won the first Nobel Prize in Chemistry (1901) for his theoretical studies of solutions and their similarities to the behavior of gases, not for the co-discovery of the asymmetric carbon. He was very much a part of the scientific establishment and remained better known than Le Bel. This chapter reminds readers that van’t Hoff’s model was flawed from logical inconsistency while Le Bel’s was correct. The chapter reports other discoveries by Le Bel and follows him through an intellectually and socially rich life until his death in 1930.

This study investigates the thermal field of S355J2+N steel plates for shipbuilding applications welded with automatic welding equipment. Real-time thermal profiles were captured and validated using infrared thermography against SolidWorks simulations. Experimental data revealed maximum weld pool temperatures of 528 °C and sharp thermal gradients in the heat-affected zone (HAZ). The numerical model, which predicts a peak temperature of 670°C, closely matched the experimental results. An empirical relationship between welding parameters and maximum welding temperature was derived, allowing optimization of heat input and welding speed to minimize thermal distortions and residual stresses. This integrated approach improves process control and weld quality in shipbuilding.

The Light Ion Analyzer (LIA) instrument, part of the Solar-wind-Magnetosphere–Ionosphere-link- Explorer (SMILE) mission, is designed to measure the ion velocity distribution function within an energy range of 5 eV up to 25 keV. LIA provides in-situ measurements of the ion velocity distribution functions of the solar wind and magnetosheath, from which the moments can be derived on the ground, serving as an upstream input for the magnetosphere-ionosphere downstream responses. Two identical 2$\pi$ sr field-of-view LIA instruments are mounted on two opposite sides of the spacecraft platform, offering a combined 4$\pi$ sr instantaneous field-of-view. Each LIA consists of a top-hat electrostatic analyzer, electrostatic aperture deflectors, and a microchannel plate detector for analyzing the energy, direction, and flux of ions. Depending on the operation mode, the angular resolution ranges from 5.625° to 22.5° in elevation and from 7.5° to 30° in azimuth, and the time resolution spans from 0.25 to 2 seconds. This paper describes the design of the LIA, its performance, ground calibration, operation procedures, and resultant data products.

Exposure to air pollution is a major cause of mortality worldwide, including in Europe, with transportation emissions being a primary contributor to urban air pollution. This article employs the impact pathway approach to quantify the monetary value of the adverse health effects of motorized two-wheelers on Parisian residents. Key pollutants are identified, and motorized two-wheelers' circulation data in Paris is spatially, temporally, and technologically disaggregated to prepare it for input into the HYSPLIT dispersion model. The total health cost borne by Paris residents due to air pollution from motorized two-wheelers in the city is estimated to be approximately €12 million per year as of 2020, representing 0.34% of the total health cost of air pollution in Paris. This relatively modest figure suggests that the majority of the adverse health effects associated with motorized two-wheelers are experienced not by Paris residents but by those in the surrounding areas.

Neural networks have been used for the retrieval of soil moisture (SM) from microwave observations over the last 20 years. The exploitation of the SMOS (Soil Moisture and Ocean Salinity) observations has largely benefited from such statistical models. However, these retrievals are currently done at the pixel level, ignoring spatial context and using a constant incidence angle configuration approach. While pixels are seen with a varying number of angles from the SMOS instrument, only pixels monitored by a fixed pre-selected angle configuration are considered. These two limitations can have a negative impact on the quality of the retrievals. This paper introduces a new NN architecture that combines two powerful innovations. Firstly, the new model is image-based: it ingests entire SMOS orbit swath and thus leverages the strong spatial pattern present in the satellite observations. Secondly, a “partial convolutional layer” is tested. It allows being flexible, in the retrieval, on the angle configuration: more incidence angles can be exploited when they are available. Finally, a concept called “Localization” is also exploited, helping the NN retrieval to adapt his behaviour to specific local conditions Experiments are conducted at SMOS orbit scale over the contiguous united states (CONUS) region using five years of SMOS data (2016–2019). A temporal correlation of 0.74 (unit-less) with respect to ERA5 reanalysis and 0.62 with respect to in situ SM measurements network are obtained (to be compared to respectively 0.63 and 0.60 with the legacy pixel and fixed angle based approach). Furthermore, the use of partial convolutions results in enlarging the retrieval domain by +240% versus legacy retrieval, and by +140% versus the operational SMOS Level-2 product.

Despite significant efforts towards extending the AGM paradigm of belief change beyond finitary logics, the computational aspects of AGM have remained almost untouched. We investigate the computability of AGM contraction on non-finitary logics, and show an intriguing negative result: there are infinitely many uncomputable AGM contraction functions in such logics. Drastically, we also show that the current de facto standard strategies to control computability, which rely on restricting the space of epistemic states, fail: uncomputability remains in all non-finitary cases. Motivated by this disruptive result, we propose new approaches to controlling computability beyond the finitary realm. Using Linear Temporal Logic (LTL) as a case study, we identify an infinite class of fully-rational AGM contraction functions that are computable by design. We use Büchi automata to construct such functions, and to represent and reason about LTL beliefs.

The purpose of the present paper is to numerically investigate the steady flow of Herschel–Bulkley fluid through thin layers in order to analyze the behavior of the rigid zones. This study establishes correlations between the measure of rigid zones, the yield stress, and the layer thickness. The results show that the increase in the yield stress leads to a large expansion of rigid zones, which becomes larger as the layer becomes thinner. Moreover, the occupancy rate and the spatial distribution of the unyielded regions within the flow domain are illustrated, showing the trend of growth of these areas until reaching an upper limit. In addition, the flow is examined under both velocity and pressure boundary conditions, which allows us to demonstrate that the blocking phenomenon corresponding to the total solidification of the flow domain occurs in the pressure-driven case, while it cannot be reached when the flow is governed by imposed velocity.

Rapid urbanization and climate change are critical processes that affect groundwater resources, particularly in urban areas. This study investigates the long-term impacts of both processes on the potential natural groundwater recharge from precipitation across the period 1986–2100 under SSP2-4.5 and SSP5-8.5 pathways. The approach used in this study combines three models, including (1) a Cellular Automata-Artificial Neural Network (CA-ANN)-based modeling for the continuous mapping of future spatiotemporal land use-land cover (LULC) distributions, (2) climate change modeling using CMIP6 GM, and (3) hydrological modeling using the Soil Conservation Service-Curve Number method (SCS-CN). The findings indicate that the urban area is anticipated to increase from 18.2% of the total area in 1986 to 86.5% by 2100 at the expense of other land cover. Moreover, projected climate change indicators derived from precipitation exhibit declining trends in yearly precipitation and extreme event frequency and intensity against an increasing dry conditions trend during the period 2017–2100. The analysis reveals a fluctuating future potential natural groundwater recharge with decreasing trends under both climate change pathways. The regression analysis shows that 27.5% (R² = 0.8199) and 24.7% (R² = 0.7867) of precipitation contribute to natural recharge under SSP2 and SSP5, respectively, highlighting a strong linear correlation between them. In comparison to a high emission pathway, these slopes indicate that achieving a moderate emission pathway will increase the potential recharge by 2.8%. In addition, the outcomes demonstrate that future groundwater recharge patterns are more sensitive to changes in climatic conditions than to urbanization. This study underscores the importance of integrating urban planning and water resources management strategies to ensure the long-term groundwater sustainability in urban cities.

Wall slip sensitivity and non-sphericity and orientation effects are investigated for a moving no-slip solid body immersed in a fluid above a plane slip wall with a Navier slip. The wall–particle interactions are examined for the body motion in a quiescent fluid (resistance problem) or when freely suspended in a prescribed ‘linear’ or quadratic ambient shear flow. This is achieved, assuming Stokes flows, by using a boundary method which reduces the task to the treatment of six boundary-integral equations on the body surface. For a wall slip length $\lambda$ small compared with the wall–particle gap d a ‘recipe’ connecting, at $O((\lambda /d)^2),$ the results for the slip wall and another no-slip wall with gap $d+\lambda$ is established. A numerical analysis is performed for a family of inclined non-spheroidal ellipsoids, having the volume of a sphere with radius a, to quantity the particle behaviour sensitivity to the normalised wall slip length $\overline {\lambda }=\lambda /a,$ the normalised wall–particle gap ${\overline {d}}=d/a$ and the particle shape and orientation (here one angle $\beta ).$ The friction coefficients for the resistance problem exhibit quite different behaviours versus the particle shape and $({\overline {d}}, \overline {\lambda },\beta ).$ Some coefficients increase in magnitude with the wall slip. The migration of the freely suspended particle can also strongly depend on $({\overline {d}}, \overline {\lambda },\beta )$ and in a non-trivial way. For sufficiently small $\overline {d}$ a non-spherical particle can move faster than in the absence of a wall for a large enough wall slip for the ambient ‘linear’ shear flow and whatever the wall slip for the ambient quadratic shear flow.

Die Verteidigungsausgaben werden in den nächsten Jahren substantiell steigen. Dieser Artikel greift auf Ergebnisse der finanzwissenschaftlichen Forschung zurück, um Herausforderungen für eine effiziente Finanzierung dieser Ausgaben zu identifizieren. Zentrale Ergebnisse sind: (i) Die Bereitschaft für höhere Verteidigungsausgaben Steuern zu zahlen, hängt auch vom Design des Sozialstaats ab. (ii) Sowohl „Pareto-Effizienz“ als auch „Politische Realisierbarkeit“ setzen der Möglichkeit Grenzen, zusätzliche Verteidigungsausgaben durch Ausgabenkürzungen an anderer Stelle zu finanzieren.

The synthesis of dibenzothiophene derivatives through a deglucosylative C-H thiolation reaction is reported. This methodology enables products to be obtained in good yields under relatively mild operating conditions.

Contrasting sharply with traditional money, bond, and bond futures markets, where interest rates emerge organically from participant interactions, DeFi lending platforms employ rule‐based interest rates that are algorithmically set. Thus, the selection of an effective interest rate model (IRM) is paramount for the success of a lending protocol. This paper investigates the modeling of agents' behaviors on lending platforms and proposes a theoretical framework for formulating optimal IRMs. We show that, under perfect information, an optimal control model with a state constraint generates an optimal interest rate policy that has a shape similar to that of popular markets. Furthermore, we formally analyze interest rate policies based on PID controllers, which work efficiently based on fewer assumptions. Using public data of popular markets on the Ethereum blockchain, we analyze agents' behavior, build a realistic simulation environment, and highlight the main tradeoffs in the design of interest rates for decentralized lending platforms.

A bstract A search for a heavy pseudoscalar Higgs boson, A, decaying to a 125 GeV Higgs boson h and a Z boson is presented. The h boson is identified via its decay to a pair of tau leptons, while the Z boson is identified via its decay to a pair of electrons or muons. The search targets the production of the A boson via the gluon-gluon fusion process, gg → A, and in association with bottom quarks, $\text{b}\overline{\text{b}}\text{A }$ . The analysis uses a data sample corresponding to an integrated luminosity of 138 fb − 1 collected with the CMS detector at the CERN LHC in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=13$ TeV. Constraints are set on the product of the cross sections of the A production mechanisms and the A → Zh decay branching fraction. The observed (expected) upper limit at 95% confidence level ranges from 0.049 (0.060) pb to 1.02 (0.79) pb for the gg → A process and from 0.053 (0.059) pb to 0.79 (0.61) pb for the $\text{b}\overline{\text{b}}\text{A }$ process in the probed range of the A boson mass, m A , from 225 GeV to 1 TeV. The results of the search are used to constrain parameters within the ${\text{M}}_{\text{h},\text{EFT}}^{125}$ benchmark scenario of the minimal supersymmetric extension of the standard model. Values of tan β below 2.2 are excluded in this scenario at 95% confidence level for all m A values in the range from 225 to 350 GeV.

The increasing computing power and bandwidth of FPGAs opens new possibilities in the field of real-time processing of high-energy physics data. The LHCb experiment has implemented a cluster-finder FPGA architecture aimed at reconstructing hits in its innermost silicon-pixel detector onthe-fly during readout. In addition to accelerating the event reconstruction procedure by providing it with higher-level primitives, this system enables further opportunities. LHCb triggerless readout architecture makes these reconstructed hit positions available for every collision, amounting to a flow of 10¹¹ hits per second, that can be used for further analysis. In this work, we have implemented a set of programmable counters, counting the hit rate at many locations in the detector volume simultaneously. We use these data to continuously track the motion of the beams overlap region and the relative position of the detector elements, with precisions of µm and time granularity of (ms). We show that this can be achieved by simple linear combination of data, that can be executed in real time with minimal computational effort. This novel approach allows a fast and precise determination of the beamline position without the need to reconstruct more complex quantities like tracks and vertices. We report results obtained with pp collision data collected in 2024 at LHCb.

Mueller matrix polarimetry (MMP) provides valuable structural insights into tissue and holds promise for medical diagnostics. However, its clinical adoption is hindered by labor-intensive data collection and annotation. This study examines the use of MMP data collected in reflection from ex vivo human brain tissue to identify neoplastic regions. Using a custom-built single-wavelength MMP imaging system, we compare deep learning models trained on Mueller matrix measurements against Lu-Chipman feature maps. Our networks achieve segmentation accuracy comparable to multi-spectral polarimetry, highlighting the potential of real-time MMP for brain tumor differentiation. We further provide a qualitative analysis discussing challenges and opportunities for neurosurgical MMP applications.

When operated at sufficiently high pressures, inductively coupled plasmas (ICPs) can produce intense gas heating which is useful for a range of applications including materials processing, gas conversion, and analytical chemistry. However, the use of physical measurement probes can be challenging inside ICPs because of the high-temperature plasma-gas environment and diagnostic access may often be limited or perturb the system. Non-invasive diagnostics, such as optical emission spectroscopy (OES), are therefore attractive alternatives but often require an associated mathematical model for complete analysis and interpretation. In this work, we present a collisional-radiative model (CRM) of a radio-frequency (RF) ICP operating with argon gas and terminated with a supersonic nozzle. The two-temperature model considers 20 different charged and neutral particle species, and accounts for important collisional (such as excitation and de-excitation), radiative (including radiation trapping), and diffusive processes. The CRM is coupled to a global plasma discharge model that enables the temperatures and species population densities to be self-consistently determined as a function of ICP operating conditions (such as mass flow rate, RF power, and nozzle size). The coupled model is compared with both a simplified analytical theory and experimental measurements obtained with several non-invasive diagnostics (including OES and electrical circuit probes) showing good agreement. The system is found to be non-equilibrium even near atmospheric pressure conditions, although the model electron temperature is close to the measured argon excitation temperature indicating at least partial local thermodynamic equilibrium between electrons and excited neutral states.