Automatic terminology or term extraction (ATE) is a Natural Language Processing (NLP) task intended to automatically identify specialized terms present in domain-specific corpora. As units of knowledge in a specific field of expertise, extracted terms are not only beneficial for several terminographical tasks, but also support and improve several complex downstream tasks, e.g., information retrieval, machine translation, topic detection, and sentiment analysis. ATE systems and datasets annotated for the task at hand have been studied and developed for decades, but more recent approaches have increasingly involved novel neural systems. Despite a large amount of new research on ATE tasks, systematic survey studies covering novel neural approaches are lacking, especially when it comes to the usage of large-scale language models (LLMs). We present a comprehensive survey of neural approaches to ATE, focusing on transformer-based neural models and the recent generative approaches based on LLMs. The study also compares these systems and previous ML-based approaches, which employed feature engineering and non-neural supervised learning algorithms.
Passiflora cincinnata is traditionally used for the management of anxiety-related disorders; however, experimental evidence supporting its neuropharmacological effects remains limited. The present study evaluated the anxiolytic-and antidepressant-like effects of the crude ethanolic extract (Pc-EtOH) obtained from the aerial parts in mice, as well as explored possible mechanisms involved. Male Swiss mice were treated orally with Pc-EtOH (100, 200, or 400 mg/kg) and submitted to a battery of behavioral tests, including the elevated plus maze, open-field, forced swimming, and tail suspension tests. Pc-EtOH at 100 mg/kg produced significant anxiolytic-and antidepressant-like effects, comparable in magnitude to reference drugs in specific parameters, without inducing motor impairment. In contrast, the highest dose (400 mg/kg) was associated with reduced locomotor activity, suggesting sedative effects. Pharmacological antagonism assays indicated a partial involvement of the GABAergic system. These findings suggest that P. cincinnata exhibits dose-dependent neurobehavioral effects, with a favorable profile at lower doses.
In this work, we propose an improved discretization, in terms of stability and accuracy, for the incompressible two-phase Darcy flows in a heterogeneous porous medium with discontinuous capillary forces. For this purpose, the total velocity formulation of the model is used. The coupled system is composed of a degenerate parabolic equation for the non-wetting phase and a pressure equation for the total velocity. We combine a positive Vertex Approximation Gradient (VAG) type scheme for the gradient fluxes with a hybrid upwinding of the mobilities. This approach entails a maximum principle on the saturations, which remain in their physical ranges. Energy estimates are obtained by selecting key approximations of the fluxes. These stability results allow to prove the existence of discrete solutions. Numerical experiments on complex test-cases show the robustness of the new approach in terms of the accuracy as well as the nonlinear convergence. Comparison to the usual phase potential upwinding approach and to a previous hybrid upwinding scheme are also provided.
In this paper we study the convergence of the positivity-preserving discrete duality finite volume (PP-DDFV) scheme introduced in Crozon et al. (2025, Positivity-preserving DDFV scheme for compressible two-phase flow in porous media. Comput. Math. Appl., 194, 110-134). It approximates solutions to the immiscible compressible two-phase Darcy flow in anisotropic porous media with a degeneracy of the mobilities. The primary variables are the physical pressures, and the phase density depends on its own pressure. Additionally, the considered two-dimensional mesh is quite general including nonconforming, as well as distorted partitions. We propose a new penalization term because it is required in the DDFV framework to force the primal and dual parts of the global pressure and the capillary terms to converge towards the same limit. As a consequence, all the results are adapted to show that the approximated solutions converge to a weak solution of the diphasic model, up to a subsequence. This is made due to the compactness arguments of type Lions-Aubin-Simon theorem. In the end, we present some typical numerical tests to exhibit the good convergence of the numerical scheme and the impact of the penalization term on the solution behaviour.
The impact of climate change on key environmental variables is well-known; yet its effect on complex phenomena such as corrosion due to carbonation and chloride ingress remains a subject of ongoing debate. While several studies have examined these processes individually, the interaction between carbonation and chloride penetration in reinforced concrete structures is less understood. Chloride ion ingress is particularly relevant in marine environments, where salt spray and carbonation may occur concurrently. Similarly, structures in urban areas exposed to de-icing salts and high $CO_2$CO2 levels due to traffic and pollution face increased corrosion risks. Previous research suggests that carbonation can significantly influence chloride ion transport in concrete, but its exact effect-whether it accelerates or decelerates damage-varies across studies. Some models estimate that the probability of corrosion initiation under combined carbonation and chloride ingress conditions may be nearly twice as high compared to considering these mechanisms separately. Therefore, understanding this interaction is crucial for improving durability predictions and developing effective mitigation strategies. This study reviews key experimental and modeling research addressing the combined effects of carbonation and chloride penetration in concrete structures.
