Gustave Eiffel University

A low‐cost high‐responsivity design of Si/SiGe heterojunction bipolar phototransistor (HPT) built in an industrial 55 nm‐BiCMOS technology is integrated in a cascode configuration with a bipolar transistor (HBT) to be used for microwave‐photonic communication receivers. Performances of both the cascode pair and the single heterojunction bipolar phototransistor are compared. At high‐frequency, the cascode circuit has better performances than the single HPT stage. At 850‐nm wavelength, the pair can reach a low‐frequency responsivity of 3.24 A/W and a bandwidth of 0.69 GHz when coupling losses are corrected.

Wastewater has been identified as one of the main contributors to microplastic (MP) pollution in aquatic environments. Hence, this study investigates the presence, characteristics of MPs in wastewater sample types (industrial, domestic, and medical wastewater), and also the removal efficacy of MPs by local wastewater treatment stations. Overall, industrial wastewater showed a higher MP abundance level at 60,881 ± 48,154 items/m³, compared to domestic and medical wastewater with values of 31,494 ± 10,142 items/m³ and 35,453 ± 13,186 items/m³, respectively. Fiber and fragment were the main shapes observed among the MPs found in all wastewater samples, and the dominant form was microfiber, ranging from 63 to 97.5% of total MPs. The performance of local wastewater treatment stations showed varied efficiencies in MP removal, ranging between 15.8 ± 5 and 90.2 ± 1.3%. Domestic wastewater treatment stations showed lower MP removal effectiveness, at 43.9 ± 13.1%, while treatment stations receiving industrial and medical wastewater achieved 59.5 ± 20.7 and 69.6 ± 22.1% of removal efficiencies, respectively. As estimated, 2.9 × 10¹⁰ microplastic items could be emitted to the water bodies around Hanoi every day, which MPs originated from domestic wastewater accounted for 80.3% due to its high discharge volume and inadequate treatment capacity. Optimization of the septic tank system operation and the sewage sludge treatment processes could prevent secondary contamination of MPs, while an additional primary sedimentation step could improve the overall MP elimination efficacy of the studied treatment stations. The results from this study suggested that more in-depth investigations were required for a proper understanding of the migration routes of MPs from different anthropogenic activities to wastewater.

The inherent porosity of usual C-S-H and C-A-S-H phases renders them inherently vulnerable to freeze-thaw damage. In this chapter, we introduce an innovative strategy, organic–inorganic assembly, to enhance the cryogenic stability of usual C-S-H. We show a way to regulating the pore structure and stiffness of C-S-H by bonding polymeric chains with silicate chains, which succeeds in eliminating micro and mesopores in C-S-H and markedly enhancing its stiffness. A hierarchical CSH@polymer composite with high Young’s modulus and low-porosity microstructure is obtained. The composite shows a hierarchically aligned superstructure with no microporosity. These remarkable microstructural and mechanical features yield the super good cryogenic stability of C-S-H superstructure.

This chapter explores how the chemical composition of C-S-H affects its cryogenic stability, specifically examining its nanostructure and nanomechanical properties. It provides a comprehensive analysis of C-S-H’s structural and physical stability under cryogenic conditions, focusing on the following aspects: the microscopic morphological variations; the transformation process and mechanisms affecting its nanostructure; the influence of Ca/Si ratios on the stability of nanomechanical properties; the evolution of C-S-H pore structures across scales during cryogenic exposure. Through multiscale characterization techniques, we analyzed the multiscale structural features of C-S-H under cryogenic attack, revealing a bottom-up degradation pathway under this harsh condition.

In this chapter, we will discuss the scaling of the nanoscopic elastic and tensile failure properties of C-S-H. We describe a Zhurkov-like scaling behavior for disordered C-S-H of various compositions at cryogenic temperatures, using molecular dynamics simulations. To this end, we begin with proposing a revised molecular construction route to generate C-S-H atomic configurations with varying compositions. Then, we present how the tensile behavior evolves with temperature, system size, and strain rate. We will show that tensile strength, Young’s modulus, fracture energy, and fracture-process zone (FPZ) length, all follow a Zhurkov-like scaling law providing a general temperature-size-time equivalence. Such scaling laws make it possible to extrapolate molecular simulation results to larger length and/or time scales.

In this chapter, we will show how C-S-H pore structure evolves under cyclic cryogenic attack. The cryogenic attack impacts on the pore structure of C-S-H were comprehensively evaluated by nitrogen adsorption measurement. With this technique, we extracted fruitful pore structure information, including pore size distribution, pore volume, specific surface area, segmented surface fractality and pore tortuosity. C-S-H gels with various chemical compositions were discussed here. The pore size distribution and pore volume were determined using the Brunauer–Emmett–Teller (BET) method and the density functional theory (DFT) approach. By using Dubinin-Radushkevich (DR) and DFT approaches, the micropore information was additionally obtained. Specific surface area was calculated using the BET approach, and the segmented surface fractal dimension was determined using the Frenkel-Halsey-Hill (FHH) model. In addition, the tortuosity was also computed using the CPSM model, which provided additional evidence to estimate the cryogenic attack's influence on the pore structure of C-S-H.

In this chapter, we present a comprehensive overview of various characterization methods employed to explore the micro and nanostructure of cement-based materials. From traditional techniques to cutting-edge advancements, a multitude of analytical methods are utilized to delve deep into the intricate world of cement-based materials, helping us to understand their properties at different length scales. The advanced techniques for characterizing the composition, morphology, pore structure, nanostructure, and nanomechanical properties are introduced here.

In this chapter, we endeavor to present a comprehensive overview of research and developments related to the formation, micro/nanostructure, and properties of C–S–H. By integrating insights from different scales, from atomistic scale to microscale, we aim to provide an elementary understanding of C–S–H in this chapter. Some basic concepts related to C–S–H micro/nanostructure will be introduced here. In particular, the classical chemical-structural and microstructure models of C–S–H are summarized. This makes it easier to discuss the cryogenic stability of C–S–H in following chapters.

In this chapter, we will discuss the potential of aluminum incorporation in C-S-H for enhancing its cryogenic stability. It systematically analyzes the atomistic structure of calcium-aluminosilicate-hydrate (C-A-S-H) with varying calcium and aluminum contents, revealing the stability of low-aluminum and high-aluminum C-A-S-H nanostructures under cryogenic attack. It turns out that the atomistic structure of low-aluminum C-A-S-H can remain stable, which enhances the stability in C-S-H pore structure and nanomechanical properties. Moreover, the presence form of aluminates in C-A-S-H is discussed here, further expanding the understanding of the existing C-A-S-H nanostructures. A DNA-code rule is introduced to describe and construct molecular models of C-A-S-H. We also propose a generalized structural-chemical formula for C-A-S-H models which can describe both cross-linked and non-cross-linked structures.

In this chapter, we move our insight on the freezing liquid in cement pores. The freezing of pore water significantly impacts the deterioration of cement concrete materials under freezing–thawing conditions. For the pore water, the crystallization of ice in confined space can exert significant pressure on the solids. Given that the porous cementitious materials have a wide distribution of pore sizes, the larger pores freeze before the smaller pores. This nonequilibrium process is therefore accompanied by cryo-suction, in which the frozen large spaces suck liquid water from the unfrozen spaces through the nanometric unfrozen water film. The thermodynamic analysis indicates that the cryo-suction occurring in the pore space can lead to the cryo-swelling of porous solids. Herein, we present an atomistic view for the active processes of ice crystallization and liquid transport.

Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning architecture designed for automatically segmenting the cortical and trabecular compartments in 3D µCT scans of mouse tibiae. DBAHNet’s hierarchical structure combines transformers and convolutional neural networks to capture long-range dependencies and local features for improved contextual representation. We trained DBAHNet on a limited dataset of 3D µCT scans of mouse tibiae and evaluated its performance on a diverse dataset collected from seven different research studies. This evaluation covered variations in resolutions, ages, mouse strains, drug treatments, surgical procedures, and mechanical loading. DBAHNet demonstrated excellent performance, achieving high accuracy, particularly in challenging scenarios with significantly altered bone morphology. The model’s robustness and generalization capabilities were rigorously tested under diverse and unseen conditions, confirming its effectiveness in the automated segmentation of high-resolution µCT mouse tibia scans. Our findings highlight DBAHNet’s potential to provide reliable and accurate 3D µCT mouse tibia segmentation, thereby enhancing and accelerating preclinical bone studies in drug development. The model and code are available at https://github.com/bigfahma/DBAHNet.

We develop the model theory of $\omega$-stable K-loops and symmetric spaces. Continuing Poizat’s seminal work, we notably establish an appropriate version of the indecomposability theorem and we adapt Lascar’s analysis to this context.

This paper investigates an approximate block factorization technique for efficiently solving large saddle point systems derived from the discretization of the Navier–Stokes equations. The standard upper triangular approximation is revisited with the addition of a lower block, specifically designed to improve system conditioning and accelerate iterative solver convergence. Numerical experiments highlight the robustness and efficiency of the lower-upper triangular approximation as a preconditioning strategy, particularly in massively parallel environments. The method proves especially effective for simulating multiphase flows with high density and viscosity ratios, complex droplet dynamics, and significant interface deformations.

In this article, we investigate the behaviour of a cohesive granular material in a rotating drum. We use a model material with tuneable cohesion and vary the dimension of the drum in the radial and axial directions. The results show that the geometry of the drum may play a crucial role in the material dynamics, leading to significant changes in the surface morphology and flow regime. We attribute this behaviour to the fact that an increase in cohesion causes the grains to feel the sidewalls at a greater distance. Finally, we rationalize the results by introducing two dimensionless characteristic lengths, defined as the ratio of the drum dimensions to a cohesive length, which allow for the interpretation of the variation in the surface morphology and of the different flow regimes observed experimentally.

This report presents a new proposal for conducting the water capillary absorption test of hemp concretes and establishing the parameters useful for analyzing the obtained results. Based on the standards of traditional materials such as concrete and mortar, a testing protocol was developed and executed by eight laboratories from RILEM TC 275-HDB through interlaboratory testing. Homogeneous cubic specimens of hemp concrete with an edge length of 150 mm were cast and distributed to the laboratories, where they were conditioned before undergoing test. By adopting the new testing procedure, consistent results were achieved after analyzing data in both square root of time and log-time regimes. For each regime, two pairs of parameters CA and k (square root of time regime), and IRA and K1 (log-time regime) were utilized to compare the data and successfully validate the interlaboratory testing.

This essay is concerned with a class of higher-order models for the unidirectional propagation of small amplitude long waves on the surface of an ideal fluid derived in [3]. These models go beyond the classical first-order theory that goes back to Boussinesq [7] and Korteweg and de Vries [13] in the $19^{th}$ century. In the water waves context, the latter models are proven to be good approximations of the two-dimensional Euler equations in regimes where their derivation is valid. However, the time scale of their validity extends only to about ten wavelengths or so. The second-order models considered here are formally accurate on the order of a hundred wavelengths. And they do not require auxiliary data beyond what the first-order models need. Nor are they computationally much more complicated than the first-order models. As a consequence, they appear to be worth extended study. Mathematical theory for the initial-value problems for these models begins already with [3] and is considerably improved in [4]. However, in the last-mentioned paper, which can countenance localized initial data as rough as the $L^2(\mathbb R)$-based Sobolev class $H^1({\mathbb {R}})$, there are some annoying restrictions if one wants the problem to be globally well-posed. These restrictions are herewith removed.

Wearable technologies represent a strong development axis for various medical applications and these devices are increasingly used in daily life as illustrated by smart watches’ popularisation. Combined with new data processing methods, it constitutes a promising opportunity for telemonitoring, triage in mass casualty situations, or early diagnosis after a traffic or sport accident. An approach to processing the physiological data is to develop severity scoring systems to quantify the critical level of an individual’s health status. However, the existing severity scores require a human evaluation. A first version of a severity scoring system adapted to continuous and real-time wearable monitoring is proposed in this article. The focus is made on three physiological parameters straightforwardly measurable with wrist-wearables: heart rate, respiratory rate, and SpO2, which may be enough to characterise continuously hemodynamic and respiratory status. Intermediate score functions corresponding to each physiological parameter have been established using a sigmoid model. The boundary conditions have been defined based on a survey conducted among 54 health professionals. An adapted function has also been developed to merge the three intermediate scores into a global score. The scores are associated with a triage tricolour code: green for a low-priority casualty, orange for a delayable one, red for an urgent one. Preliminary confrontation of the new severity scoring system with real data has been carried out using a database of 84 subjects admitted to the intensive care unit. Colour classification by the new scoring system was compared with independent physicians’ direct evaluation as a reference. The prediction success rate values 74% over the entire database. Two examples of continuous monitoring over time are also given. The new score has turned out to be consistent, and may be easily upgraded with the integration of additional vital signs monitoring or medical information.

Electric energy consumption is increasing much faster than the predicted growth in energy generation. Although the installed capacity of renewable energy sources is also expanding, grid congestion remains unavoidable without adopting smart energy management systems (EMS) and flexible power electronics structures. Given the significant installed capacity of photovoltaic (PV) systems in the residential sector, moving towards zero-emission buildings (ZEBs) through the use of storage systems and smart power electronics is essential. This article provides a detailed review of power electronics solutions for ZEBs and offers strategies to address related challenges. By exploring the promising future of the low-voltage dc (LVDC) industry in ZEBs, it presents and compares grid connection scenarios and evaluates their overall efficiencies across hybrid, dc, and ac technologies. Furthermore, it addresses the integration of dc and ac systems in energy resources (ER), proposing solutions for challenges related to protection, grounding, and leakage currents. Finally, it examines the latest EMS solutions, emphasizing the shift to full digitalization through a combination of cloud-based and edge-computing platforms.