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Objective(s): The present study aimed to explore the mechanisms underlying the potency of the renoprotective effect of the EtOAc fraction of Limonium duriusculum (EALD) (Plumbaginaceae) against cyclosporine A (CsA), in comparison to vitamin E (Vit. E).Materials and Methods: In the in-vivo experiment, a model of CsA-induced nephrotoxicity was established by dosing male Wistar rats with 25 mg/kg, for 14 days. The protective effect of EALD was investigated through pretreatment of rats with a dose of 200 mg/kg for 14 days, compared to the oral administration of Vit. E at 100 mg/kg. Renal function and markers of oxidative stress were then assessed. Furthermore, a complementary in-vitro study was carried out to evaluate CsA-induced endoplasmic reticulum stress (ERS) and inflammation on cell culture (3T3 cells and MCT cells) using western blot and quantitative RT-PCR..Results: Pretreatment of rats with EALD significantly attenuated the elevated levels of renal dysfunction markers (BUN, creatinine) and suppressed malondialdehyde (MDA) levels; It also significantly regulated the changes in superoxide dismutase (SOD), reduced glutathione (GSH), glutathione peroxydase (GPx), and glutathione S-transferase (GST) levels as compared to Vit. E, demonstrating a more effective recovery in renal tissues. Treatment of cells with CsA was linked to the expression of ERS and inflammatory markers activating transcription factor (ATF4), inositol-requiring enzyme 1α (IRE1α), binding immunoglobulin protein (BiP), and monocyte chemoattractant protein-1 (MCP1). In contrast, pretreatment of cells with EALD resulted in a significant decrease in both ERS and inflammatory markers.Conclusion: These findings indicate the renoprotective potential of L. duriusculum, as it demonstrated the ability to ameliorate CsA-induced renal dysfunction through its distinctive antioxidant properties.

Objective(s): The current study was conducted to assess the protective mechanisms of n-BuOH fraction from the aerial part of Genista cephontala (BEGC) on APAP-induced liver injury compared to necrostatine-1 (Nec-1).Materials and Methods: A model of APAP-induced hepatotoxicity was created in male rats by injecting a single dose; 1000 mg/kg APAP, the protective effect was performed with (200 mg/kg; 10 days) BEGC compared to Nec-1, (1.8 mg/kg).Results: BEGC or NeC-1 pretreatment significantly abolished impaired effects in APAP-rats, by decreasing the generation of TBARS and ROS in mitochondrial and cytosolic fractions and maintaining liver function activities. A marked response was observed in the levels of both GSH and GSH-system enzymes in liver homogenates and mitochondrial fractions to BEGC. BEGC/ Nec-1 successfully regulated the inflammatory mediators (IL-β, TNF-α, HMGB1, and acHMGB1) and MPO levels. During APAP treatment, no caspase-3 or -8 activity was detected, and the level of fk18; M30 was higher than the levels of cck18; M65. Moreover, RIPK3 and MLKL levels were increased in the APAP group. These results suggested that necroptosis predominates during the APAP liver injury model. Interestingly, these necroptotic factors were significantly down-regulated by BEGC treatment. Both biochemical and histopathological findings were consistent with each other.Conclusion: From all these findings, the hepatoprotective effect of BEGC could be due to the abundance of polyphenols identified by LC-MS/MS analysis, as well as the synergistic interactions of all contents.

Silver, typically acknowledged for its inertness toward hydrogen under standard conditions, exhibits a noteworthy shift in reactivity under elevated pressures. Employing first-principles variable-composition evolutionary search calculations, our investigation unveils the presence of thermodynamically stable Ag-H compounds. A novel stoichiometry, Ag2H, characterized by P3¯m1 symmetry, emerges as the thermodynamically stable phase at 100 GPa. Notably, the trigonal-Ag2H phase at 100 GPa demonstrates both mechanical and dynamic stability, as ascertained through the computation of elastic constants and phonon dispersions, respectively. Examination of the electronic band structure and density of states manifests the metallic nature of the resulting Ag2H compound. A comprehensive analysis involving crystal orbital bond index, Bader charge, and charge density plots substantiates the ionic character of Ag2H, attributable to effective charge transfer from silver atoms to hydrogen. Furthermore, application of the Allen-Dynes modified McMillan equation indicates the absence of superconducting behavior in Ag-H systems at the elevated pressure of 100 GPa.

La tumeur fibreuse pleurale solitaire, longtemps considérée fibrome pleural ou mésothélium fibreux localisé, est une tumeur mésenchymateuse rare, représentant 5% des masses pleurales. Le premier cas a été rapporté en 1931 par Klemperer et Rabin; 800 cas sont rapportés dans la littérature jusqu’à 2010, dont deux grandes séries: Briselli (USA, 1981, 360 cas et England (USA, 1989) ,223 cas, les autres séries ne dépassant pas 30 cas[1]. Elle est réputée bénigne, souvent bien limitée, encapsulée, guérissant après exérèse complète.

Currently, Electric Arc Furnace Slag (EAFS) is undervalued and is therefore only used in road construction, while blast furnace slag (BFS) is used as an interesting alternative in construction materials to replace natural aggregates in the manufacture of concrete. Steel slag (SS) represents a promising secondary resource due to its high content of critical metals, such as chromium (Cr) and vanadium (V). These metals are essential for various strategic industries, making it crucial to consider slag as a resource rather than waste. However, the primary challenge lies in selectively recovering these valuable metals. In this work, we explore the development of a hydrometallurgical process aimed at efficiently extracting Cr and V from Electric Arc Furnace Slag (EAFS). The characterization of the investigated EAFS shows that the main crystalline phases contained in this heterogeneous material are srebrodolskite, larnite, hematite, and spinel such as probably magnesio-chromite. The targeted metals seem to be dispersed in various mineral species contained in the SS. An innovative hydrometallurgical method has been explored, involving physical preparation by co-grinding slag with alkaline reagents followed by treatment in a microwave furnace to modify the metal-bearing species to facilitate metal processing dissolution. The results obtained showed that the leaching rates of Cr and V were, respectively, 100% and 65% after 15 min of treatment in the microwave furnace, while, after 2 h of conventional heat treatment, as explored in a previous study, 98% and 63% of the Cr and V were, respectively, leached.

Résumé : En didactique, l'activité de la dictée est une tâche liée à l’orthographe. Cette dernière est considérée comme un moyen permettant l’acquisition des compétences orthographiques sous ces différentes formes. Elle a pour objectif de vérifier la maitrise des savoirs orthographiques déjà étudiés en classe. En plus, cette activité donne une occasion aux élèves pour le réinvestissement de leur pré requis. Notre article se veut une réflexion sur le rôle de la dictée comme une activité de remédiation aux erreurs orthographiques. Nous opterons pour la méthode expérimentale où nous nous appuierons sur la double démarche : analytique et comparative pour analyser les copies des élèves. Mots-clés : dictée ; orthographe ; remédiation ; élèves 5AP ; erreurs

In petroleum domain, optimizing hydrocarbon production is essential because it does not only ensure the economic prospects of the petroleum companies, but also fulfills the increasing global demand of energy. However, applying numerical reservoir simulation (NRS) to optimize production can induce high computational footprint. Proxy models are suggested to alleviate this challenge because they are computationally less demanding and able to yield reasonably accurate results. In this paper, we demonstrated how a machine learning technique, namely long short-term memory (LSTM), was applied to develop proxies of a 3D reservoir model. Sampling techniques were employed to create numerous simulation cases which served as the training database to establish the proxies. Upon blind validating the trained proxies, we coupled these proxies with particle swarm optimization to conduct production optimization. Both training and blind validation results illustrated that the proxies had been excellently developed with coefficient of determination, R2 of 0.99. We also compared the optimization results produced by NRS and the proxies. The comparison recorded a good level of accuracy that was within 3% error. The proxies were also computationally 3 times faster than NRS. Hence, the proxies have served their practical purposes in this study.

Gas injection has emerged over the recent decades as a promising technology to enhance oil recovery in various fields worldwide. The efficiency and success of a gas injection operation can be assessed through a number of vital experimental studies. Interfacial Tension (IFT) between the injected gas and the displacing fluid is a key parameter playing an eminent role in the foregoing studies. The main scope of this work is making a progress in modeling the IFTs between diverse n-alkanes and Methane (CH4), Carbon Dioxide (CO2), and Nitrogen (N2) natural gases. For this purpose, two smart AI-based approaches of Cascaded Feedforward Neural Network (CFNN) and Decision Tree Learning (DT) were used to simultaneously model the IFTs between foregoing immiscible binary systems as a function of pressure, temperature, the gases properties, and the properties of the liquid. Several statistical measures and graphical descriptions were employed to aid the accuracy analysis of the proposed models. Both developed CFNN and DT networks represented desirable close-to-reality predictions in all binary systems. Besides, CFNN established itself as the most robust model for all studies binary systems with RMSE values of 0.5924, 0.5649, and 0.5870 mN/m, and R2 values of 0.9902, 0.9910, and 0.9904 for the train, test, and overall data, respectively.

Aim: Discontinuity in the distribution of genetic diversity (often based on mtDNA) is usually interpreted as evidence for phylogeographic breaks, underlying vicariant units. However, a misleading signal of phylogeographic break can arise in the absence of barrier to gene flow, under mechanisms of isolation by distance (IBD). How and under which conditions phylogeographic breaks can be reliably differentiated from populations evolving under IBD remain unclear. Here, we use multi-locus sequence data from a widely distributed lizard species to address these questions in an empirical setting. Location: Morocco. Taxon: Spiny-footed lizard (Acanthodactylus erythrurus), Squamata: Lacertidae. Methods: Using 325 samples from 40 localities, we identified genetic discontinuities within A. erythrurus based on a mitochondrial fragment and nine nuclear markers independently. Using the nuclear markers, we then applied linear regression models to investigate whether genetic divergence could be explained by geographical distances alone, or barriers to gene flow (real phylogeographic breaks). Results: A. erythrurus is characterized by an important mitochondrial diversity, with 11 strongly supported phylogeographic lineages with a crown age of 6 Mya. Nuclear markers, however, yielded weak phylogenetic support for these lineages. Using clustering methods based on genotypes at nine nuclear loci, we identified phylogeographic clusters that were partly discordant with the mtDNA lineages. Tests of IBD delimited at least four groups of populations separated by barriers to gene flow, but unambiguous separation of vicariance from IBD remained challenging in several cases. Main conclusions: The genetic diversity of A. erythrurus originates from a mix of IBD and vicariance, which were difficult to distinguish, and resulted in similar levels of mitochondrial differentiation. These results highlight that phylogeographic breaks inferred from mitochondrial data should be further investigated using multi-locus data and explicit testing to rule out alternative processes generating discontinuities in mitochondrial diversity, including IBD. We identified four groups of populations within A. erythrurus, separated by barriers to gene flow, but even using nine independent nuclear makers the power of our approach was limited, and further investigation using genome-wide data will be required to resolve the phylogeographic history of this species.

Accurate prediction of wax deposition is of vital interest in digitalized systems to avoid many issues that interrupt the flow assurance during production of hydrocarbon fluids. The present investigation aims at establishing rigorous intelligent schemes for predicting wax deposition under extensive production conditions. To do so, multilayer perceptron (MLP) optimized with Levenberg-Marquardt algorithm (MLP-LMA) and Bayesian Regularization algorithm (MLP-BR) were taught using 88 experimental measurements. These latter were described by some independent variables, namely temperature (in K), specific gravity, and compositions of C1–C3, C4–C7, C8–C15, C16–C22, C23–C29 and C30+. The obtained results showed that MLP-LMA achieved the best performance with an overall root mean square error of 0.2198 and a coefficient of determination (R2) of 0.9971. The performance comparison revealed that MLP-LMA outperforms the prior approaches in the literature.

Currently, Electric Arc Furnace Slag (EAFS) is undervalued and is therefore only used in road construction, while blast furnace slag (BFS) is used as an interesting alternative in construction materials to replace natural aggregates in the manufacture of concrete. Steel slag (SS) represents a promising secondary resource due to its high content of critical metals, such as chromium (Cr) and vanadium (V). These metals are essential for various strategic industries, making it crucial to consider slag as a resource rather than waste. However, the primary challenge lies in selectively recovering these valuable metals. In this work, we explore the development of a hydrometallurgical process aimed at efficiently extracting Cr and V from Electric Arc Furnace Slag (EAFS). The characterization of the investigated EAFS shows that the main crystalline phases contained in this heterogeneous material are srebrodolskite, larnite, hematite, and spinel such as probably magnesio-chromite. The targeted metals seem to be dispersed in various mineral species contained in the SS. An innovative hydrometallurgical method has been explored, involving physical preparation by co-grinding slag with alkaline reagents followed by treatment in a microwave furnace to modify the metal-bearing species to facilitate metal processing dissolution. The results obtained showed that the leaching rates of Cr and V were, respectively, 100% and 65% after 15 min of treatment in the microwave furnace, while, after 2 h of conventional heat treatment, as explored in a previous study, 98% and 63% of the Cr and V were, respectively, leached. [ABSTRACT FROM AUTHOR]

As energy demand continues to rise and conventional fuel sources dwindle, there is growing emphasis on previously overlooked reservoirs, such as tight reservoirs. Shale and coal formations have emerged as highly attractive options due to their substantial contributions to global gas reserves. Enhanced shale gas recovery (ESGR) and enhanced coalbed methane recovery (ECBM) based on gas injection are advanced techniques used to increase the extraction of gas from shale and coal formations. One of the key challenges associated with these formations and their enhanced recovery methods is accurately predicting the sorption process and its profile. This is crucial because it affects how methane (CH4) and carbon dioxide (CO2) are stored and released from the rock, and it significantly impacts the evaluation of gas content and the potential productivity of these formations. Due to the high cost of experimental procedures and the moderate accuracy of existing predictive approaches, this study proposes various cheap and consistent data‐driven schemes for predicting the sorption of CH4 and CO2 in shale and coal formations. In this regard, three intelligent models, including generalized regression neural network (GRNN), radial basis function neural network (RBFNN), and categorical boosting (CatBoost), were taught and tested using more than 3800 real measurements of CH4 and CO2 sorption in shale and coal formations. To find automatically their appropriate control parameters and improve their prediction ability, RBFNN and CatBoost were evolved using grey wolf optimization (GWO). The obtained results exhibited the encouraging prediction capabilities of the suggested models. In addition, it was found that CatBoost‐GWO is the most accurate scheme with total root mean square (RMSE) and determination coefficient (R2) of 0.1229 and 0.9993 for CO2 sorption, and 0.0681 and 0.9970 for CH4 sorption, respectively. Additionally, this approach demonstrated its physical validity by respecting the real sorption tendencies with respect to operational parameters. Furthermore, the CatBoost‐GWO model outperforms recently published machine learning approaches. Lastly, the findings of this study offer a significant contribution by demonstrating that the suggested model can greatly improve the ease of estimating CO2 and CH4 sorption in tight formations, thereby facilitating the simulation of other parameters related to this process. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]