University of Orléans

Healthcare workspaces can greatly benefit from the employment of robotic assistants in both clinical and non-clinical tasks. However, despite their advantages, a major shortcoming for the deployment of such robotic solutions, limiting their widespread market acceptance, is the fact that they were originally designed for large industrial and warehouse spaces. These are characterized by structured spaces and predictable environments, where robots move along predefined paths and interaction with humans is typically minimal. Herein, state-of-the-art computer vision methods are examined, which enable robots to detect the presence and identify the type of dynamic obstacles inside their visual field, so that they can adapt their navigation accordingly. For this purpose, the COCO128 dataset was augmented with an extra category consisting of nursing robots. Then, a new custom dataset was generated, comprising images of humans and a range of logistics/ nursing robots, captured within realistic hospital settings. Robotic vision systems were trained using contemporary deep learning methods (namely the YOLO—You Only Look Once—architecture and its variations) obtaining promising results in both human and robot detection. Ultimately, the goal of this study is to contribute towards safe robot navigation in healthcare spaces and the deployment of robotic fleets in less structured environments.

While the literature on internationalization in Africa is growing, much of it has traditionally emphasized the role of multinational corporations operating on the continent. In contrast, fewer studies have focused on the international entrepreneurial activities of indigenous African firms, particularly, in relation to how internal capabilities interact with external institutional environments. This study addresses this gap by drawing on dynamic capabilities theory and the institutional perspective to examine how firm‐level capabilities influence export performance under varying conditions of institutional support and perceived corruption. Based on survey data from 192 exporting firms across nine African countries, the results show that the effects of vigilant market capability and open marketing capability on export performance are significantly moderated by institutional and environmental factors. These findings contribute to the literature on international firm performance in emerging markets and offer practical insights for strategy and policy development in the African context.

Influenza in France causes, on average, more than 1 million primary care consultations, 20,000 hospitalizations, and 9000 deaths annually. Adults over 50 years of age face higher risks of severe influenza due to increasing chronic conditions associated with aging, yet vaccination rates in this group are low, as recommendations start from age 65. This study explores the potential health and economic benefits of expanding vaccination recommendations to individuals aged 50 and over. Using the literature and French health insurance data, a SEIR (susceptible–exposed–infectious–recovered) model was developed. The subpopulations were stratified by age, vaccination status, and risk profile. Various expanded vaccination strategies were compared to the current strategy, assessing impacts on epidemiological outcomes (consultations, hospitalizations, deaths), economic metrics (vaccination costs, medical care expenses), and quality-adjusted life years (QALY). The model's robustness was tested with deterministic and probabilistic sensitivity analyses. Expanded vaccination recommendations for individuals over 50 years of age lead to an average reduction of 500,124 consultations, 9486 hospitalizations, and 2990 deaths, with an associated additional cost of 58 million euros compared to the current vaccination strategy. The cost-effectiveness analysis estimates an incremental cost-effectiveness ratio (ICER) of €1496/QALY. When considering indirect costs, the total savings in this expanded vaccination scenario amount to €– 314,308,377, resulting in a dominant ICER. This indicates that the strategy would not only be more cost-effective but also cost-saving compared to the current approach. Expanding vaccination recommendations for low-risk adults over 50 is cost-effective and represents a significant public health opportunity.

Background Cancer represents a complex group of diseases characterized by abnormal cell proliferation, invasion, and metastasis. These features pose significant challenges to conventional therapeutic approaches, necessitating the development of more targeted and effective treatment strategies. Objective This review aims to explore the potential of selenium nanoparticles (SeNPs) as a novel therapeutic tool in cancer treatment, emphasizing their cytotoxic mechanisms and advantages over conventional therapies and other nanoparticles. Methods The review synthesizes findings from recent studies investigating the therapeutic properties of SeNPs in cancer models. Emphasis is placed on their ability to selectively target malignant cells, modulate redox status, and influence tumor‐associated cellular processes such as autophagy and microRNA regulation. Results SeNPs demonstrate intrinsic antioxidant properties that counteract oxidative stress commonly observed in cancer cells. They modulate critical cellular pathways and exhibit selective toxicity, damaging cancer cells while sparing healthy tissues. Additionally, their biocompatibility and capacity to deliver therapeutic agents contribute to improved safety and efficacy compared to other nanoparticle platforms. Conclusion Selenium nanoparticles hold significant promise as a next‐generation cancer treatment modality. Their dual function—serving as both therapeutic agents and drug delivery vehicles—positions them as a powerful tool in precision oncology. By minimizing off‐target effects and enhancing targeted drug delivery, SeNPs have the potential to advance the landscape of cancer theragnostics.

Sodium dual-ion batteries combine economic and environmental benefits by using carbon materials in both electrodes and sodium compounds in the electrolyte. Among other factors, their successful implementation for energy storage relies on optimization of the properties of the carbon electrode materials. To this end, carbon materials with a wide range of textural and structural properties were prepared by simply heat treating a single porous carbon in the absence or presence of a low-cost highly effective iron-based catalyst. These materials were investigated as anode or cathode in the sodium dual-ion batteries by prolonged galvanostatic cycling. The optimal textural and structural properties for carbon materials to achieve the best performance as electrodes in sodium dual-ion batteries were identified as having a high degree of graphitic structural order combined with minimal microporosity in the cathode and a non-graphitic structure with a layer spacing of around 0.37 nm and moderate microporosity in the anode.

In the context of minimally invasive surgical procedures using miniaturized robots (endovascular catheter, endoscopic capsule, etc.), magnetic actuation is a promising solution for non-contact navigation of these tools. In this work, we develop and validate an electromagnetic actuation system that combines the advantages of existing systems, notably in terms of workspace, control and accessibility of the magnetic field. This is an electromagnetic coil with an optimized ferromagnetic core carried by a 7 Degrees of Freedom (DoF) collaborative robotic arm. In addition to the static magnetic field, this system generates a rotating magnetic field. However, this type of actuator requires a high-current power supply and generates undesirable Joule-effect heat. A specialized cooling system was therefore developed to solve the problem of overheating. The design of the electromagnetic actuator and its cooling system were constrained by the desired magnetic performance and ranges, the robot’s capabilities, and temperature evolution. The prototype’s performances in terms of electromagnetism, cooling and magnetic actuation were experimentally validated.

This paper investigates the dynamic response of water‐saturated concrete under high stress levels, with a particular emphasis on the role of pore pressure. An enhanced elastoplastic damage model, incorporating dual plastic mechanisms, is proposed to capture the coupled hydromechanical behavior of concrete under combined high stress and high strain rate loading. Key improvements include the refinement of the porosity‐volumetric strain relationship, the incorporation of full hydromechanical coupling under dynamic loading, and the integration of strain rate sensitivity into the pore collapse mechanism and material strength. The improved constitutive model and numerical methodology are validated through simulations of uniaxial tensile tests and three sets of compression tests. Parametric studies are conducted to explore the influence of pore pressure on the confined response of concrete under both static and dynamic loading conditions. The results demonstrate that interstitial pore pressure significantly affects both the volumetric and deviatoric behaviors of saturated concrete, with its influence becoming more pronounced under dynamic loading. The findings provide valuable insights into the hydromechanical behavior of concrete structures subjected to extreme loading scenarios.

Using recycled aggregates in concrete and mortar reduces environmental impact by minimizing both natural aggregate consumption and construction waste disposal. 3D printing offers innovative, cost-efficient construction methods, but it heavily relies on cement and sand. This research aims to investigate the hard properties of 3D printing mortars made with 100% substitution of natural sand by recycled sand. The effects of sand substitution and 3D printing process on the hard properties of printable mortars are studied. The mechanical strength of moulded and printed specimens of printable mortars based on recycled sand were studied and compared with those made from a reference printable mortar based on natural sand. Additionally, the microstructure of mortars, namely the density of the interfacial transition zone in these specimens was analysed to understand the mechanical strength results. The results showed that both the incorporation of recycled sand and the 3D printing process had little effect on the mechanical strength. This could be attributed to the decrease in the density of the interfacial transition zone caused by both the incorporation of recycled sand and the mortar printing process. Furthermore, the study investigated also the effect of incorporating recycled sand on autogenous, drying, and total shrinkage. It was observed that this incorporation reduces the autogenous shrinkage at an early age, while it increases both dry and total shrinkage.

Herein, the synthesis of imidazo[1,2‐a]pyridines, imidazo[1,2‐a]pyrazines and imidazo[1,2‐b]pyridazines by a multicomponent Groebke–Blackburn–Bienaymé reaction is described under sustainable conditions using eucalyptol as green solvent. After determining the optimum conditions for catalysis, a library of 32 compounds with activity on the central nervous system was quickly and efficiently assembled.

The detection of Terrestrial Gamma ray Flashes (TGFs) from space is mostly made by astrophysics satellites, which only provide single‐point measurements. Future TGF missions could consist in performing simultaneous detection by a detector array in space. In order to prepare such a scientific objective, we simulate the detection of TGFs by a nanosatellite, or small satellite, constellation. The objective is to quantify the impact of six parameters defining such a constellation, in order to maximize the scientific return of the mission. The parameters characterized in this work are the number of satellites, their relative distance, their altitude, their orbital configuration, the effective detection surface, and their orbital inclination. We use a Monte Carlo simulation code to propagate photons in the atmosphere and simulate the satellite positions and photons hits on satellites. Finally, we quantify the number of TGFs detected by the fleet, multi‐detected, the number of photons received, and draw conclusions about the impact of each parameter.

The World Health Organization (WHO) has recognized Particulate Matter (PM) as the main threat to human health from air pollution. One of the solutions is Green Infrastructure (GI), which uses different plants to mitigate pollution. Among these plants are bryophytes (or more commonly used mosses), which have easier maintenance, lighter weight, and durability compared to vascular plants. However, currently, there is limited knowledge of its effectiveness in air pollution mitigation. By addressing this gap in current scientific knowledge, more effective deployment of GI could be introduced by municipalities for society’s health benefits. This study aimed to evaluate three species of mosses (Dicranum scoparium, Plagiomnium affine, and Hypnum cupressiforme) and one thuja (Thuja plicata) as a control species for a possible GI vertical barrier for local de-pollution. The objective was to assess different moss species’ effectiveness in air pollution PM2.5 and PM10 absorption in a laboratory setting. The practical experiment was conducted from June–July 2024 in the Laboratory of the Physics and Chemistry of Environment and Space in Orleans (LPC2E-CNRS), France. For the experiment, a unique air pollution chamber was engineered and built with a linear barrier of GI inside to measure pollution absorption before and after the barrier. With the obtained data from the sensors, the efficiency of the vegetation barrier was calculated. The total average efficiency of all 18 tests and tested moss species is 41% for PM2.5 and 47% for PM10 mass concentrations. Efficiency shows moss species’ maximum or optimal ability to absorb pollution PM2.5 and PM10 in laboratory environments, with the limitations indicated in this article. This research is an essential step towards further and more profound research on the effectiveness of GI barriers of mosses in urban environments. It significantly contributes to understanding GI effects on air pollution and presents the results for specific moss species and their capacity for PM2.5 and PM10 mitigation in the air. The novelty of the study lies in a particular application of the chosen moss species.