University of Upper Alsace

This study presents the development and evaluation of five dyes with varying conjugated energy levels and donor‐π‐acceptor (D‐π‐A) structures as photoinitiators for free radical polymerization. Their photoinitiation efficiencies are systematically assessed under both visible‐light LED and sunlight. Notably, the conversions reach up to 81% within just 30 s under sunlight, demonstrating the ultra‐fast and efficient polymerization capabilities of the dyes. The efficient electron transfer is facilitated by the D‐π‐A structure, where the conjugation is reduced or interrupted by the high distortion between the electron‐withdrawing and the electron‐releasing units. This distortion can prevent the overlap of frontier molecular orbitals, decreasing the energy difference between the ground state and the excited state of dyes, thereby enhancing the electron transfer reactivity with additives. Additionally, we propose a chemical mechanism for the electron transfer reaction in the three‐component systems. The study also explores the application of naphtho[2,3‐d]thiazole‐4,9‐dione‐based dyes as donors in additive manufacturing demonstrating their effectiveness in three different 3D printing technologies, i.e. direct laser writing (DLW), digital light processing (DLP), and liquid crystal display (LCD). These three‐component formulations achieve high‐precision 3D printed objects, with detailed characterization and comparison of the resulting structures.

This study presents the development and evaluation of five dyes with varying conjugated energy levels and donor‐π‐acceptor (D‐π‐A) structures as photoinitiators for free radical polymerization. Their photoinitiation efficiencies are systematically assessed under both visible‐light LED and sunlight. Notably, the conversions reach up to 81% within just 30 s under sunlight, demonstrating the ultra‐fast and efficient polymerization capabilities of the dyes. The efficient electron transfer is facilitated by the D‐π‐A structure, where the conjugation is reduced or interrupted by the high distortion between the electron‐withdrawing and the electron‐releasing units. This distortion can prevent the overlap of frontier molecular orbitals, decreasing the energy difference between the ground state and the excited state of dyes, thereby enhancing the electron transfer reactivity with additives. Additionally, we propose a chemical mechanism for the electron transfer reaction in the three‐component systems. The study also explores the application of naphtho[2,3‐d]thiazole‐4,9‐dione‐based dyes as donors in additive manufacturing demonstrating their effectiveness in three different 3D printing technologies, i.e. direct laser writing (DLW), digital light processing (DLP), and liquid crystal display (LCD). These three‐component formulations achieve high‐precision 3D printed objects, with detailed characterization and comparison of the resulting structures.

A bstract In the era of precision measurements of neutrino oscillation parameters, it is necessary for experiments to disentangle discrepancies that may indicate physics beyond the Standard Model in the neutrino sector. KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study the oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on the initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photosensors. A high-purity neutrino sample was extracted during 2020 and 2021, corresponding to an exposure of 433 kton-years. This sample is analysed following a binned log-likelihood approach to search for invisible neutrino decay, in a three-flavour neutrino oscillation scenario, where the third neutrino mass state ν 3 decays into an invisible state, e.g. a sterile neutrino. The resulting best fit of the invisible neutrino decay parameter is ${\alpha}_3={0.92}_{-0.57}^{+1.08}\times {10}^{-4}$ α 3 = 0.92 − 0.57 + 1.08 × 10 − 4 eV ² , corresponding to a scenario with θ 23 in the second octant and normal neutrino mass ordering. The results are consistent with the Standard Model, within a 2.1 σ interval.

Vehicular ad hoc networks (VANETs) are very changeable networks due to the highly dynamic movement of their nodes, resulting in frequent link disconnection and variable node density. One of the most challenging issues in VANETs is to propose a suitable routing scheme that is adapted to the characteristics of such a dynamic topology. Position‐based routing schemes that are effective in handling dynamic changes in the topology of VANETs are proposed. This article proposes an efficient routing protocol based on a greedy forwarding approach called ERGF. The proposed protocol is a position‐based routing protocol that uses fresh vehicular traffic information in the routing process. ERGF consists of two main algorithms: the vehicle traffic freshness dissemination algorithm and the greedy forwarding algorithm. The both algorithms work together to provide fresh, up‐to‐date information about vehicle traffic, enabling the proposed routing protocol to effectively withstand dynamic changes in VANET network topology. The proposed protocol has been developed over OMNET++ simulator, evaluated and compared with some other protocols. The simulation results showed that the proposed protocol provided better performance in terms of packet delivery rate and end‐to‐end delay than the EGyTAR and PBRP protocols. The packet delivery ratio of our proposal is approximately 75% and 6% higher than EGyTAR and PBRP, respectively, and the end‐to‐end delay of our protocol is reduced by 37% and 7%, respectively, compared with EGyTAR and PBRP for most scenarios.

Diazomethyl-λ³-iodanes have recently emerged as carbyne equivalents in organic synthesis, enabling the construction of multi-substituted carbon centers through strategic sequential activation of the diazo and iodane functional groups. Distinct from such reaction modes, we report here on the reactivity of diazomethyl-λ³-iodanes as iodane-bound 1,3-dipoles toward arynes. Equipped with bis(trifluoromethyl)benzyl alcohol-based benziodoxole (BX) moiety, diazomethyl-λ³-iodanes undergo annulation with arynes generated from ortho-silylaryl triflates and cyclic diarylhalonium salts, resulting in indazolyl-λ³-iodanes through [3 + 2] cycloaddition and carbon-to-nitrogen iodane migration. DFT calculations reveal that diazomethyl-BX prefers [3 + 2] cycloaddition with aryne over aryne insertion into the carbon–iodine(iii) bond (carboiodanation) and that the subsequent iodane migration proceeds through two consecutive 1,5-iodane shifts. The utility of these indazolyl-BXs as indazole-transfer agents has been demonstrated by α-functionalization of N,N-dimethylaniline derivatives.

The use of natural fibers as recyclable and environmentally friendly materials in technologically advanced products such as composites is widely increasing. Automated tape-laying (ATL) technology is one of the more widely used manufacturing techniques for composites, as it allows process interruptions and facilitates changes of direction. It is especially useful for producing components with complex contours. However, the density and width of the tape-laying preforms, along with the laying angle, can influence the process, potentially leading to defects such as wrinkles. This paper investigates a new approach to mitigating these defects by analyzing the deformation patterns of nonwoven fiber strips during tape-laying through an in-plane bending model. Optical measurements in plane tape-laying tests evaluate the effects of laying path direction, tape width, and elastic modulus on bending resistance. Results show that at a room temperature of 25 °C and a uniform laying rate, fabric tapes exhibit no more than 10% tensile or compressive strain during initial stretching. The high deformation potential of nonwoven is further demonstrated, as large curvature paths can be laid without visible defects when the correct dimensional parameters and reinforcement orientation are chosen. Additionally, a mechanical model based on bias theory is proposed to provide geometric optimization solutions for ATL performs.

Whatever the final use, usual or composite materials, 2D or 3D fabrics, high-density weaving processes cause yarn-to-yarn friction damage, leading to filament breakage and interlacing, resulting in defects in the final product and reducing production speed. The study aimed to highlight the specific weaving pattern configurations that are harmful to yarns by measuring directly on the weaving machine yarn tension and tracking movement, both focused on the shedding stage. A new paradigm for defining the weaving pattern based on yarn interactions is considered, with three parameters: the number of moving yarns, the number of potential yarn interactions, and the pattern organisation for the same number of moving yarns. From a spectral analysis of yarn tension evolution during the weaving cycle and the yarn speed study, it can be concluded weaving pattern criticality depends on a combination of both the number of moving yarns and the number of crossings between them. Principal Component Analysis highlights the correlation between parameters.

A bstract A standard model effective field theory (SMEFT) analysis with dimension-six operators probing nonresonant new physics effects is performed in the Higgs-strahlung process, where the Higgs boson is produced in association with a W or Z boson, in proton-proton collisions at a center-of-mass energy of 13 TeV. The final states in which the W or Z boson decays leptonically and the Higgs boson decays to a pair of bottom quarks are considered. The analyzed data were collected by the CMS experiment between 2016 and 2018 and correspond to an integrated luminosity of 138 fb − 1 . An approach designed to simultaneously optimize the sensitivity to Wilson coefficients of multiple SMEFT operators is employed. Likelihood scans as functions of the Wilson coefficients that carry SMEFT sensitivity in this final state are performed for different expansions in SMEFT. The results are consistent with the predictions of the standard model.

The main purpose of this paper is to introduce and investigate the notion of Jacobi–Jordan conformal algebras. They are a generalization of Jacobi–Jordan algebras which correspond to the case in which the formal parameter λ equals 0. We consider some related structures such as conformal modules, corresponding representations and O-operators. Therefore, conformal derivations from Jacobi–Jordan conformal algebras to their conformal modules are used to describe conformal derivations of Jacobi–Jordan conformal algebras of the semidirect product type. Moreover, we study a class of Jacobi–Jordan conformal algebras called quadratic Jacobi–Jordan conformal algebras, which are characterized by mock-Gel’fand–Dorfman bialgebras. Finally, the C[∂]-split extending structures problem for Jacobi–Jordan conformal algebras is studied. Furthermore, we introduce an unified product of a given Jacobi–Jordan conformal algebra J and a given C[∂]-module K. This product includes some other interesting products of Jacobi–Jordan conformal algebras such as the twisted product and crossed product. Using this product, a cohomological type object is constructed to provide a theoretical answer to the C[∂]-split extending structures problem.

Differential equations form the basis of consecutive equations in the field of engineering sciences, in particular in mechanics and material sciences. In fact, the use of rheological constitutive equations incorporating fractional derivatives has garnered significant attention over the past fifty years. Fractional derivative equations have demonstrated consistency with molecular theories [1]. In terms of thermodynamic compatibility, rheological models incorporating fractional derivatives offer a more precise fit with laboratory measurement results [2, 3]. Therefore, in this chapter, we demonstrate in a first part (Sect. 1) the interest of differential equations with fractional order in the description of the mechanical behaviour of materials. Due to its ability to absorb deformation energy, flexible polyurethane (PU) foam finds widespread usage in various comfort applications, including automotive seat cushions and mattresses. Designing a mechanical model to characterize its behaviour under different test conditions holds considerable interest for optimizing comfort of the personalized seating occupant system under static, quasi-static, and dynamic conditions. When it is subject to a significant compression deformation, PU exhibits highly nonlinear elasticity and viscoelastic behaviour. The theory of viscoelasticity holds significant importance in describing materials characterized by time-dependent mechanical behaviour. Constitutive models for small one-dimensional deformations in viscoelastic materials can be expressed in either integer or fractional differential equations. In the second part (Sect. 2) of this chapter, we focus on modelling the quasi-static behaviour of polyurethane foam using a memory integer and fractional models. The parameters of two memory models (fractional memory model and integer memory model) were determined through original minimization and identification methods. The identified parameters meet the thermodynamic conditions. The results show good agreement between experimental behaviour of polyurethane foam and those predicted by two memory models. Finally, a comparison between these models was conducted.

A bstract Measurements are presented of inclusive and differential cross sections for Z boson associated production of top quark pairs ( $\textrm{t}\overline{\textrm{t}}\textrm{Z}$ t t ¯ Z ) and single top quarks (tZq or tWZ). The data were recorded in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb − 1 . Events with three or more leptons, electrons or muons, are selected and a multiclass deep neural network is used to separate three event categories, the $\textrm{t}\overline{\textrm{t}}\textrm{Z}$ t t ¯ Z and tWZ processes, the tZq process, and the backgrounds. A profile likelihood approach is used to unfold the differential cross sections, to account for systematic uncertainties, and to determine the correlations between the two signal categories in one global fit. The inclusive cross sections for a dilepton invariant mass between 70 and 110 GeV are measured to be 1.14 ± 0.07 pb for the sum of $\textrm{t}\overline{\textrm{t}}\textrm{Z}$ t t ¯ Z and tWZ, and 0.81 ± 0.10 pb for tZq, in good agreement with theoretical predictions.

In RPL-based IoT networks, especially at the edge where devices are highly constrained, security challenges are increasingly prominent. The core functionality of RPL does not inherently include mechanisms to detect or mitigate security attacks. Simulations demonstrate that blackhole attacks significantly degrade network performance, reducing Packet Delivery Ratio to as low as 24.74% and increasing latency up to 2.42 s.This paper addresses this gap by proposing a novel lightweight approach for mitigating blackhole attacks using collaborative packet-based detection mechanisms. The proposed solution effectively detects and mitigates these attacks, improving PDR to 88.86%, reducing latency to 0.595 s, and maintaining a minimal memory footprint compared to complex machine learning or heavy cryptographic RPL-based solutions. This study contributes to advancing security solutions tailored for edge-centric IoT environments, ensuring robust and reliable network operation.

Multi‐material printing has experienced critical advances in recent years, yet material property differentiation capabilities remain limited both with regard to the accessible properties – typically hard versus soft – and the achievable magnitude of differentiation. To enhance multi‐material printing capabilities, precise photochemical control during 3D printing is essential. Wavelength‐differentiation is a particularly intriguing concept yet challenging to implement. Notably, dual‐wavelength printing to fabricate hard and soft sections within one object has emerged, where one curing process is insensitive to visible light, while UV irradiation inevitably activates the entire resin, limiting true spatio‐temporal control of the material properties. Until now, pathway‐independent wavelength‐orthogonal printing has not been realized, where each wavelength exclusively triggers only one of two possible reactions, independent of the order in which the wavelengths are applied. Herein, a multi‐wavelength printing technique is introduced employing a tunable laser to monochromatically deliver light to the printing platform loaded with a fully wavelength‐orthogonal resin. Guided by photochemical action plots, two distinct wavelengths – each highly selective toward a specific photocycloaddtion reaction – are utilized to generate distinct networks within the photoresin. Ultimately, together with the printing technique, this orthogonally addressable photoresin allows fabricating multi‐material objects with degradable and non‐degradable properties, in a single fabrication step.

The increasing digitization of healthcare raises the concerns surrounding the patients' privacy. Therefore, the integration of privacy preserving technologies has proven imperative to curb the negative repercussions tied to technology deployment in the medical sector and to provide trustworthy artificial intelligence healthcare applications. Two raising approaches are promoted to the forefront of research and gaining momentum in the realm of healthcare smart systems: Federated Learning and Differential Privacy. On one hand, Federated Learning (FL) enables collaborative model training across multiple institutions without exchanging raw data. Differential Privacy (DP), on the other hand, provides a formal framework for safeguarding data against potential privacy breaches. The application of these approaches in healthcare settings ensures the protection of sensitive patient informations. In this paper, we delve into the challenges posed by medical data to see how FL and DP can be tailored to suit these requirements. We aim to strike a balance between technology deployment in the medical field and privacy preservation. To this end, we developed a Multi-layer Perceptron (MLP) model to predict if a person is at risk to have heart diseases. The model, trained on different medical datasets for heart diseases, reached an accuracy of 99.57%. The same model was trained in FL framework. It achieved a FL averaged accuracy reaching 99.15%. In a third scenario, to enhance clients' privacy, we deployed a DP framework. The differentially private MLP achieved an accuracy extending to 97.07% in centralized settings and averaged accuracy attaining 89.94% in FL settings, outperforming existing methods in heart diseases prediction .

A bstract A search is presented for a heavy resonance decaying into a Z boson and a Higgs (H) boson. The analysis is based on data from proton-proton collisions at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138 fb − 1 , recorded with the CMS experiment in the years 2016–2018. Resonance masses between 1.4 and 5 TeV are considered, resulting in large transverse momenta of the Z and H bosons. Final states that result from Z boson decays to pairs of electrons, muons, or neutrinos are considered. The H boson is reconstructed as a single large-radius jet, recoiling against the Z boson. Machine-learning flavour-tagging techniques are employed to identify decays of a Lorentz-boosted H boson into pairs of charm or bottom quarks, or into four quarks via the intermediate H → WW * and ZZ * decays. The analysis targets H boson decays that were not generally included in previous searches using the H → $\textrm{b}\overline{\textrm{b}}$ b b ¯ channel. Compared with previous analyses, the sensitivity for high resonance masses is improved significantly in the channel where at most one b quark is tagged.

In this paper, a low molecular weight lignin was separated under an alkali medium from Moroccan date palm waste. The reaction of glyoxal with the extracted lignin was studied by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-ToF) mass spectrometry for its use as a phenol substitute in Phenol–Formaldehyde (PF) wood adhesives. Glyoxal is an environment-friendly, nonvolatile and nontoxic aldehyde. Different reactions were found to occur during glyoxalation, in particular lignin depolymerization and recombination through condensation reactions with glyoxal to form glyoxalene bridges linking both lignin units and mainly fractions of lignin units derived from degradation during depolymerization. Solid state CP MAS ¹³C NMR (Nuclear magnetic resonance) analysis confirmed the presence of functional groups pertaining to structures that are formed from glyoxalation of the lignin observed by MALDI-ToF. The mass spectrometry appears to be a suitable method for examining lignin-glyoxal reactions. Graphical Abstract

A bstract A search for dark matter (DM) particles produced in association with bottom quarks is presented. The analysis uses proton-proton collision data at a center-of-mass energy of $\sqrt{s}$ s = 13 TeV, corresponding to an integrated luminosity of 138 fb − 1 . The search is performed in a final state with large missing transverse momentum and a pair of jets originating from bottom quarks. No significant excess of data is observed with respect to the standard model expectation. Results are interpreted in the context of a type-II two-Higgs-doublet model with an additional light pseudoscalar (2HDM+a). An upper limit is set on the mass of the lighter pseudoscalar, probing masses up to 260 GeV at 95% confidence level. Sensitivity to the parameter space with the ratio of the vacuum expectation values of the two Higgs doublets, tan β , greater than 15 is achieved, capitalizing on the enhancement of couplings between pseudoscalars and bottom quarks with high tan β .

A bstract Differential cross sections for top quark pair ( $\textrm{t}\overline{\textrm{t}}$ t t ¯ ) production are measured in proton-proton collisions at a center-of-mass energy of 13 TeV using a sample of events containing two oppositely charged leptons. The data were recorded with the CMS detector at the CERN Large Hadron Collider and correspond to an integrated luminosity of 138 fb − 1 . The differential cross sections are measured as functions of kinematic observables of the $\textrm{t}\overline{\textrm{t}}$ t t ¯ system, the top quark and antiquark and their decay products, as well as of the number of additional jets in the event. The results are presented as functions of up to three variables and are corrected to the parton and particle levels. When compared to standard model predictions based on quantum chromodynamics at different levels of accuracy, it is found that the calculations do not always describe the observed data. The deviations are found to be largest for the multi-differential cross sections.

A bstract A search for long-lived heavy neutral leptons (HNLs) using proton-proton collision data corresponding to an integrated luminosity of 138 fb − 1 collected at $\sqrt{s}$ s = 13 TeV with the CMS detector at the CERN LHC is presented. Events are selected with a charged lepton originating from the primary vertex associated with the proton-proton interaction, as well as a second charged lepton and a hadronic jet associated with a secondary vertex that corresponds to the semileptonic decay of a long-lived HNL. No excess of events above the standard model expectation is observed. Exclusion limits at 95% confidence level are evaluated for HNLs that mix with electron and/or muon neutrinos. Limits are presented in the mass range of 1–16.5 GeV, with excluded square mixing parameter values reaching as low as 2 × 10 − 7 . For masses above 11 GeV, the presented limits exceed all previous results in the semileptonic decay channel, and for some of the considered scenarios are the strongest to date.