Université Polytechnique Hauts-de-France

Objectives Virtual reality (VR) is increasingly being used for sports purposes, including tactical learning. However, the instructional efficiency of this emerging technology remains unclear, especially when considering learners’ cognitive abilities, such as visuospatial abilities (VSA). The aim of this study was to investigate the role of VSA in memorizing soccer tactics under immersive (VR) and non-immersive (animation) conditions. Methods The experiment involved a group of 52 adult male soccer beginners. Initially, participants’ VSA were assessed using six computerized tasks. Subsequently, participants were tasked with memorizing and reproducing tactical soccer scenes in VR and animation formats. Results The results revealed a significant interaction, indicating that beginners with high-VSA were more efficient at memorizing scenes through animation than VR, supporting the ability-as-enhancer hypothesis. Conversely, those with low-VSA benefited equally from both visualizations, despite being more accurate in recalling scenes through VR. Conclusions Findings suggest that coaches should pay attention when using new technologies such as VR and consider individuals’ levels of VSA to improve their communication and learning sessions.

The realization of integrated, low-loss, and efficient systems for data-intensive applications such as augmented and virtual reality requires on-chip integrated photonic circuits, which have great potential for advanced information and communication technologies, including 6G wireless networks and intra- and inter-chip communication systems. A promising platform for achieving this revolution is Valley Photonic Crystals (VPCs). VPCs enable the construction of topological interfaces, which facilitate the propagation of light with minimal losses and backscattering through unidirectional edge modes. Interfacial topological interfaces and the degree of topological protection experienced by these robust edge modes is a relatively new perspective worth exploring. The ever-increasing demand for faster data rates in data-intensive applications like augmented and virtual reality necessitates the exploration of frequencies beyond the conventional 300 GHz band. In this study, we introduce variations in topological protection by considering different interfacial designs and suitable air-hole geometries for passive functional devices. We show that the partial breakup of topological protection can be an asset for the design of on-chip passive functionalities. We focus on bearded and zigzag junctions and appropriate air hole geometries for VPC unit cells. To experimentally verify the scalability of topological protection, we demonstrate the performance of terahertz (THz) topological ring resonators and THz double cavity resonators designed for operation in the 600 GHz frequency region. This work showcases how the scaling of topological protection can be achieved by utilizing a combination of air hole geometry and interfacial degrees of freedom, providing functional tuning of devices at the chip level.

In recent years, fused deposition modeling (FDM) techniques have become essential for the future of additive manufacturing. One of the main challenges is to identify the optimal printing parameters that enhance the quality, productivity, and durability of the resulting structures. Although hardness is critical for mechanical strength and wear resistance, it has been little studied in polylactic acid (PLA) structures. This study addresses this gap by evaluating the impact of FDM process parameters on microhardness using design of experiments (DOE) tools. Factors such as filling strategy, extrusion temperature, and layer count were analyzed. Response surface methodology (RSM) and ANOVA analyses were employed to develop a decision-support strategy. Vickers microhardness was measured for various PLA samples under different 3D printing conditions. In this context, by correlating structural homogeneity with microhardness, a performance index was established to maximize microhardness while minimizing heterogeneity. The study identified optimal printing conditions: a ZIGZAG filling strategy, an extrusion temperature of 230 °C, and four layers, each with a thickness of 0.2 mm. These conditions allowed for an increase in the microhardness of PLA structures by up to 400%, with a microhardness variability of less than 16% (more homogeneous PLA structure).

For the additive manufacturing in civil engineering, the cementitious ink must have contradictory properties to be printable, indeed it must be initially fluid enough to be pumpable and extrudable, and also should stiffen quickly after deposition to be buildable. These can influence the mechanical properties and the behavior of the printed structure. This work is focused on the role of the printing conditions, mainly time gap between successive layers and environmental conditions, on the quality of the interface between printed layers. The mechanical properties of the interface were studied by means of classical and instrumented indentation tests at micro and macroscopic scales jointly to bidirectional macro compression tests. In addition to the macrohardness tests, microindentation allows to study the role of the interface at a local scale by applying the interfacial weakness criterion based on a hardness profile established on a cross-section in the neighborhood to the plane of the interface. The influence of the printing conditions on the mechanical behavior of the interface is clearly highlighted. As an example, this criterion shows a degradation of the interface property with an increase in the time gap between layers in addition to the influence of the thermo-hygrometric conditions. For a better understanding of the mechanical behavior at the interface, additional instrumented indentation tests in the plane of the interface using macro-loads are carried out until the rupture. The critical load of fracture confirms the role of the printing conditions, whereas the compression tests are not able to show significant differences between the elaboration conditions. The indentation test, which is not widespread in the field of civil engineering, proves here that it can be very useful for a finest mechanical characterization of the material, especially for the characterization of the interface at a local scale.

Flows over cavities are relevant to many branches of engineering and are known to be a source of instabilities, high-pressure disturbances, and large recirculating regions, leading to excessive pressure loads. In this paper, we study the dynamical behavior of a 6.44:1 length-to-depth transitional cavity flow (i.e., where the shear layer partly enters the cavity) with wall proximity and lateral apertures. Mitigation of pressure loads is investigated through steady blowing upstream of the cavity’s leading edge. Concurrent pressure and particle image velocimetry (PIV) measurements along with companion unsteady numerical simulations have been performed to identify the mechanisms underlying the flow dynamics of both baseline and controlled cases. Experiments are reproduced numerically using the Improved Delayed Detached Eddy Simulations (IDDES) approach with shear stress transport eddy viscosity model ($k-\omega$ SST) at a Reynolds number of $Re=2.8 \times 10^5$. Results underline that steady blowing changes the flow drastically upstream of the cavity by thickening the boundary layer and reducing the flow rate passing the cavity. The controlled flow transforms the dynamics of the cavity shear layer, impacting the inner cavity flow, and leads to a significant reduction of the pressure loads. This mitigation is associated with a strong reduction in turbulent momentum at the shear layers interface.

In the wake of the prominence of language models such as ChatGPT/GPT4 and the emergence of various Natural Language Processing (NLP) approaches, there has been growing interest in their applications. However, a gap exists in scientific documentation regarding Small and Medium Enterprises (SMEs) within the industrial sector. This paper addresses this gap. This is the first systematic review of the literature associated with the context of NLP in industry. Through five research questions, it provides an overview of NLP applications, goals, technical solutions, obstacles, and applicability to SMEs, which is useful for both researchers and manufacturers. Following the PRISMA 2020 methodology, this study reveals a lack of literature addressing the use of NLP in industrial SMEs. The findings suggest that NLP is predominantly applied in specific industrial domains, including design, process monitoring, and maintenance. NLP applications mainly aim to enhance operational performance, notably in support functions like maintenance, safety, and continuous improvement. Practical implementations include automatic data analysis, similarity searches, information retrieval, and the conversion of raw text into standardized data. When looking at the technical solutions implemented, the paper demonstrates a strong diversity in the encountered algorithmic approaches. Challenges include remaining up-to-date, scaling, addressing low-quality or insufficient data issues, and navigating domain- or operator-specific vocabulary. In particular, maintaining up-to-date data presents a critical challenge for NLP applications but with limited identified solutions. Finally, the study indicates that only a fraction of the proposed NLP algorithmic solutions may apply to SMEs because of a lack of resources, expertise, and standardized procedures.

This paper presents a novel model-free control approach, Flower Pollination Algorithm-based Model-Free Control (FPA-MFC), for trajectory tracking of mini-drone quadrotor unmanned aerial vehicles (UAVs). The proposed approach employs an adaptive estimator based on filtered signals to approximate the nonlinear dynamic functions of the system. This approximator allows the development of a robust decentralized control law able to separately manage the position and attitude dynamics of the drone. The controller design is free of any prior knowledge of the system dynamics, and the control inputs are computed solely from instantaneous input and output measurements. Indeed, this can significantly reduce the computational burden and improve the efficiency of the control algorithm while preserving its simplicity. The design gains of the control law are selected using the metaheuristic flower pollination algorithm to achieve greater trajectory tracking performance and ensure closed-loop system stability. Simulation tests conducted on the Parrot mini drone platform validate the effectiveness and superior performance of FPA-MFC, compared to similar controllers without optimization and using the particle swarm optimization algorithm.

With the growing penetration of microwave applications in modern society, exposure to electromagnetic waves (EMWs) may become an important public health problem. In addition, the coexistence of radio-frequency (RF) devices and systems induces Electromagnetic Interference (EMI) leading to electromagnetic perturbations and lifetime reduction. Consequently, shielding materials capable of blocking EMWs are highly required. In this paper, composite materials using graphene oxide (GO) and silver nanowires (AgNWs) were studied as potential EMW shielding materials. Both GO and AgNWs were synthesized and used to obtain GO-AgNWs composites with different mass ratios of GO and AgNWs (from 1:9 to 3:1, respectively). The sheet size of GO was between 150 and 2000 nm and the thicknesses of flakes in the range of 2–5 nm. UV–Vis spectroscopy proved the successful production of AgNWs and the establishing interaction of NWs with GO sheets in the produced composites. The changes in the surface hydrophilicity/hydrophobicity showed that the selected eco-friendly reduction with ascorbic acid as a reducing agent was efficient in inducing the lowering in the hydrophilicity of the GO surface, while in the case of reduced GO (rGO) functionalized with AgNWs, the contact angle was 73.6° which between rGO and GO due to AgNWs hydrophilic character. The average thickness of free-standing films was around 14.8 μm. We studied the ratio between these nanomaterials to modulate shielding efficiency in a broad microwave frequency of up to 18 GHz. The shielding efficiency of around 6.5 dB was measured for the rGO free-standing film.

Doped GeSbTe (GST)-based phase change materials are of growing interest due to their ability to enable high-temperature data retention for embedded memory applications. This functionality is achieved through Ge enrichment and addition of dopants such as N and C in stoichiometries such as GST-225, which improve the crystallization temperature and thermal phase stability. In this study, we examine the effect of these dopants on thermal conductivity using Raman thermometry. We report the temperature-dependent thermal conductivity of the amorphous and crystalline phases of Ge-rich GeSbTe (GGST) and Ge-rich GeSbTe N-doped (GGSTN) thin films. The results reveal a surprising temperature dependence of the thermal conductivity of the crystalline phase of GGST and GGSTN, a phenomenon not typically observed for GST-based materials. Additionally, enrichment of Ge and subsequent N-doping result in reduced thermal conductivity, which can benefit the power consumption of phase change memories. From a characterization perspective, Raman thermometry has been developed as a technique for simultaneous structural and thermal characterization of GST-based materials.

The absorption of sound has great significance in many scientific and engineering applications, from room acoustics to noise mitigation. In this context, porous materials have emerged as a viable solution towards high absorption performance and lightweight designs. However, their performance is somewhat limited in the low-frequency regime. Inspired by the concept of recursive patterns over multiple length scales, typical of many natural materials, here, we propose a hierarchical organization of multilayered porous media and investigate their performance in terms of sound absorption. Two types of designs are considered: a hierarchical periodic (HP) and a hierarchical gradient (HG). In both cases, it is found that in some frequency ranges the introduction of multiple levels of hierarchy simultaneously allows for: (i) an increase in the level of absorption compared with the corresponding bulk block of porous material (or to the previous hierarchical levels (HLs)), and (ii) a reduction in the quantity of porous material required. Another advantage of using this approach is on the fabrication, since only one porous material is required. The performances are examined for both normal and oblique incidences, as well as for different values of the static air-flow resistivity. The methodological approach is based on the transfer-matrix method, optimization algorithms such as the metaheuristic greedy randomized adaptive search procedure (GRASP), finite-element calculations and measurements performed in an impedance tube.

This study introduces a method for single-channel imaging at low sampling rates, utilizing Frequency-Modulated Continuous Wave radar combined with space-frequency multiplexing. This approach significantly reduces system complexity and data acquisition demands by encoding scene reflectivity into a single, low-frequency signal. A mathematical framework supporting this technique is developed and followed by an experimental demonstration, where an image is reconstructed using a transmit antenna and a 15-element receive array within the 92–96 GHz band, whose interaction is converted into a single beat signal with a 32 MHz bandwidth.

We study the free Schrödinger equation on finite metric graphs with infinite ends. We give sufficient conditions to obtain the L 1 ( R ) → L ∞ ( R ) time decay rate at least t−1/2. These conditions allow certain metric graphs with circles and/or with commensurable lengths of the bounded edges. Further we study the dynamics of the probability flow between the bounded sub-graph and the unbounded ends.

Platelet extracellular vesicles (pEVs) isolated from clinical‐grade human platelet concentrates are attracting attention as a promising agent for wound healing therapies. Although pEVs have shown potential for skin regeneration, their incorporation into wound bandages has remained limitedly explored. Herein, gelatine‐based hydrogel (PAH‐G) foams for pEVs loading and release are formulated by crosslinking gelatine with poly(allylamine) hydrochloride (PAH) in the presence of glutaraldehyde and sodium bicarbonate. The optimized PAH‐G hydrogel foam, PAH0.24G37, displayed an elastic modulus G’ = 8.5 kPa at 37 °C and retained a rubbery state at elevated temperatures. The excellent swelling properties of PAH0.24G37 allowed to easily absorb pEVs at high concentration (1 × 10¹¹ particles mL⁻¹). The therapeutic effect of pEVs was evaluated in vivo on a chronic wound rat model. These studies demonstrated full wound closure after 14 days upon treatment with PAH0.24G37@pEVs. The maintenance of a reduced‐inflammatory environment from the onset of treatment promoted a quicker transition to skin remodeling. Promotion of follicle activation and angiogenesis as well as M1–M2 macrophage modulation are evidenced. Altogether, the multifunctional properties of PAH0.24G37@pEVs addressed the complex challenges associated with chronic diabetic wounds, representing a significant advance toward personalized treatment regimens for these conditions.

In recent years, researchers have been investing intensively in the field of AI and robotics so that these robots can communicate as normally as possible with humans. These robots need to recognize human emotions to understand them and respond to their desires. We can recognize the emotion of the person either by his facial expressions, his voice, the gestures of his body or by his words. In this work we just focused on the speech, we worked with the RAVDESS corpus, which contains 8 emotions (neutral, happy, sad, fear, angry, surprise, calm and disgust). For emotion recognition, we have used deep learning which we tested two different architectures based on CNN and compared their accuracies.

Inland waterway transportation plays a crucial role in Europe's transportation network and economy. It is an efficient and sustainable mode of transportation, with lower emissions and energy consumption than other modes of transportation, such as road and air. However, the services provided by inland waterway transport can be significantly impacted by adverse weather conditions such as heavy rain, strong winds, and flooding. These disruptions can cause delays, cancellations, or even damage to vessels or infrastructure. To improve the system reliability, we propose a set of revenue management based (demand itinerary) rerouting mechanisms for intermodal barge transportation optimisation. Revenue Management policies including several customer categories and fare differentiation are applied. Sequential accept/reject decisions are made based on a probabilistic mixed integer programming model maximising the expected revenue of a carrier. A booking framework is defined over a rolling horizon and capacity allocation/reallocation decisions are made for a set of demands including the current and relevant past and potential future transportation requests. Several (demand) rerouting mechanisms are defined and implemented on different service network configurations. The service network status is regularly updated, in particular with respect to barge capacity variations due to changing water levels. An extensive set of experiments is performed and numerical results are analysed. The study results emphasise the added value but also the need for data availability and information sharing between the different stakeholders of Inland Waterway Transportation systems.