Publications Scientifiques
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Item Androgen receptor expression in triple negative breast cancer: an Algerian population study(Taylor and Francis, 2025) Hedjem, Amel; Kouchkar, Amal; Ladjeroud, Amel; Zerrouki, Nacera; Benaissa, Fatima; Ibrahim, Nasir A.; Aleissa, Mohammed Saad; Basher, Nosiba S.; Derguini, Assia; Idres, TakfarinasTriple-negative breast cancer (TNBC) is a molecular subtype of breast cancer characterized by the absence of estrogen and progesterone receptors and the lack of HER2 overexpression. TNBC is highly heterogeneous, complicating the identification of new therapeutic targets. However, the expression of the androgen receptor (AR) in the luminal androgen receptor (LAR TNBC) subgroup has opened the door to alternative therapeutic approaches. This study aimed to assess AR expression and correlate it with clinicopathological factors in 160 early-stage TNBC patients treated from February 2015 to February 2017. Our findings reveal that AR expression is observed in 16.87% (27/160) of ≥1% AR positivity cases. Moreover, a significant 12.5% (20/160) was found in ≥10% AR positive cases. Positive AR expression was inversely correlated with a high Ki-67 proliferation index and with the basal immunophenotype. The five-year survival rate for our cohort was 83.12%, and no significant association between AR expression and overall survival was observed (p = 0.77). The study highlights the potential role of AR expression in TNBC and its implications for therapeutic strategies, although no significant association with overall survival was foundItem An improved artificial neural network using weighted mean of vectors algorithm for precise GTAW weld quality prediction and parameter optimization(Springer Science and Business Media, 2026) Boucetta, Brahim; Boumediene, Faiza; Ait Chikh, Mohamed Abdessamed; Afia, AdelAccurate prediction of mechanical properties in gas tungsten arc welding (GTAW) remains challenging due to the complex, nonlinear relationships between process parameters and weld quality. This study introduces a novel framework that systematically evaluates seven state-of-the-art metaheuristic algorithms: spider wasp optimizer (SWO), weighted mean of vectors (INFO), gradient-based optimizer (GBO), artificial rabbits optimization (ARO), blood-sucking leech optimizer (BSLO), RUN beyond the metaphor (RUN), and successive history adaptive differential evolution (SHADE), for training artificial neural networks (ANNs) to predict ultimate tensile strength in GTAW of Inconel 825 alloy. The primary novelty lies in identifying the gradient-based optimizer as the most effective algorithm for this application, presenting superior generalization capability and establishing a new benchmark for welding parameter prediction. The optimized ANN-GBO model achieved significant performance improvements over conventional ANN approaches, with the coefficient of determination () increasing from 0.6844 to 0.8669 (26.7% improvement) and root mean square error (RMSE) decreasing from 51.89 MPa to 33.71 MPa (35.0% reduction). These substantial enhancements in prediction accuracy provide critical insights for optimizing high-performance nickel-based alloy welding processesItem Antifungal and anti-toxigenic activities of Origanum onites and Thymus capitatus essential oils and ethanolic extracts against mycotoxigenic fungi isolated from barley(Elsevier, 2025) Dammak, Islem; Hamdi, Zohra; Lamine, Myriam; Hajri, Haifa; Basiouni, Shereen; Ntougias, Spyridon; Tsiamis, George; Yilmaz, Mete; Acheuk, Fatma; Emekci, MevlutWith the purpose of identifying biological substances for controlling Aspergillus-caused aflatoxin B1 and ochratoxin A contamination in cereals, particularly in barley, we assessed the efficiencies of Origanum onites and Thymus capitatus essential oils (EOs) and ethanolic extracts (EEs) under in vitro conditions. NMR and GC-TOF-MS analysis revealed the metabolite profiles with carvacrol being the major component in both EOs, and various terpenes, carbohydrates, phenols, flavonoids, and alcohols in the complex EEs. All tested EOs and EEs completely inhibited mycelial growth, sporulation, and mycotoxin production in vitro, albeit at different concentrations: O. onites EO displayed higher antifungal and anti-mycotoxigenic activities than T. capitatus EO. Notably, O. onites EO effectively protected barley grains from A. flavus, A. niger, and ochratoxin A and aflatoxin B1 contamination, during storage when applied via fumigation. Antioxidant activities of EEs were generally higher than those of EOs, with O. onites EE being the most potent antioxidant mixtureItem A data driven fault diagnosis approach for robotic cutting tools in smart manufacturing(International Society of Automation, 2025) Afia, Adel; Gougam, Fawzi; Soualhi, Abdenour; Wadi, Mohammed; Tahi, Mohamed; Tahi, MohamedIn smart manufacturing within Industry 4.0, tool condition monitoring (TCM) is used to improve productivity and machine availability by leveraging advanced sensors and computational intelligence to prevent tool damage. This paper develops a hybrid methodology using heterogeneous sensor measurements for monitoring robotic cutting tools with four tool states: healthy, surface damage, flake damage and broken tooth. The proposed approach integrates the maximal overlap discrete wavelet packet transform (MODWPT) with health indicators to construct feature matrices for each tool state. Feature selection is performed using the tree growth algorithm (TGA) to reduce computation time and improve feature space separation by selecting only relevant features. The selected features are input into a Gaussian mixture model (GMM) to detect, identify and classify each tool state with high accuracy. The proposed method provides a classification accuracy of 99.04 % for vibration, 95.51 % for torque, and 91.67 % for force signals. Using unseen vibration data, the model achieved a test accuracy of 98.44 %, demonstrating a high degree of generalizability. Comparative analysis demonstrates that our proposed approach provides superior feature discrimination and model stability, balancing computational efficiency and classification accuracy, validating the TGA-GMM framework as an effective solution for tool fault diagnosis in noisy, high-dimensional data.Item Recycling used cooking oil into a biobased epoxide by experimental design using R(Routledge, 2025) Bourkaib, Nor El Houda; Irinislimane, Ratiba; Belhaneche-Bensemra, NaimaThis study investigates the optimisation of epoxidizing used cooking oil (UCO) using in-situ generated performic acid (PFA), applying a full factorial experimental design and statistical analysis in R. Key process variables included the molar ratios of C=C to hydrogen peroxide and formic acid, reaction temperature (40–60°C), and time (3–5 hours). The optimal conditions C=C:H₂O₂:HCOOH ratio of 1:2.7:0.8, 60°C, and 3 h yielded an oxirane oxygen content (OOC) of 84.2% with 96.3% selectivity. A kinetic study under these conditions revealed a pseudo-first-order reaction, with an activation energy of approximately 14.7 kcal·mol−1. These findings highlight the potential for substituting fresh oil with UCO in industrial epoxide production, promoting resource efficiency and sustainabilityItem A comparative study of Fm-3m TiO2, ZrO2, HfO2, and CeO2 via atomistic modeling(Institute of Materials and Machine Mechanics, Slovak Academy of Sciences, 2025) Mebtouche, Farouk; Abaidia, Saddik Elhak; Messaid, Bachireddine; Lamri, Younes; Nehaoua, NadiaMetal oxides (XO2) have been extensively studied experimentally and theoretically. However, atomistic insights into systems like ZrO2 and CeO2, critical in nanocatalysis, remain incomplete. Using ab initio density functional theory (DFT) with the FP-LAPW method in the Wien2k framework and the PBE exchange-correlation functional, we examined the physical and chemical properties of cubic Fm-3m oxides (XO2, X = Ti, Zr, Hf, Ce). Lattice parameters increase with atomic mass except for HfO2, which deviates due to stronger ionic bonding. ZrO2 is the stiffest, followed by HfO2, TiO2, and CeO2. Electronic analysis shows TiO2’s narrow band gap (1.15 eV), ZrO2 and HfO2’s wide gaps (3.16 and 3.77 eV), and CeO2’s moderate gap (2.17 eV) with redox activity. PDOS analysis highlights O 2p and metal d-/f-orbital interactions. These results emphasize distinct properties influencing their applications in photocatalysis, dielectrics, and catalysis, warranting further explorationItem Proactive handover for task offloading in UAVs(Elsevier, 2025) Abdmeziem, Mohammed Riyadh; Nacer, Amina Ahmed; Demil, SoumeyaUnmanned Aerial Vehicles (UAVs) are usually deployed alongside Internet of Things (IoT) devices in smart city applications, particularly for critical tasks such as disaster management that require continuous service. UAVs often handle resource-intensive and sensitive tasks through offloading, but unexpected task interruptions due to UAV dropouts can generate safety risks and increase costs. Although existing approaches in the literature have already addressed proactive handovers to mitigate such disruptions, their primary focus is on communication issues arising from UAV movement and are unable to handle offloading related issues. In this paper, we include in our model, in addition to communication, factors such as energy, computation requirements, and dynamic environmental conditions (e.g., wind speed and incentive), pushing toward a comprehensive solution for UAV task offloading and resource allocation. In fact, we formulate our problematic as a Markov game, which we solve using a Multi Agent Deep Q Network (MADQN). In our experiments, we assessed our approach using a federated learning scenario to illustrate its effectiveness in a realistic distributed application setting against several baselines from the state of the art. Results showed that our approach outperforms its peers in terms of system utility, and tradeoff between cost and dropout rates, leading to an improved handover management of computational and energy resources in UAV-IoT based systems. In fact, it reduces the dropout rate by approximately 45% compared to the second-best baseline, leading to a 2% improvement in model accuracy and a 50% reduction in deployment costsItem Electrodeposited ZnO sulfurized into ZnS-ZnO composites as a novel approach for Cd-free buffer layer in chalcogenide solar cells(Elsevier, 2025) Bencherif A.; Bousbiat E.; Bouraiou A.; Meglali O.; Zoukel A.; Derkaoui K.In this study, ZnS-ZnO composite thin films were developed as alternative buffer layers to CdS and ZnS for second-generation solar cells. ZnO thin films were initially deposited on indium tin oxide (ITO) substrates using the electrodeposition method, followed by sulfurization in sealed glass capsules containing sulfur powder at two different temperatures (500 °C and 550 °C) under an argon-neon atmosphere. The structural, compositional, morphological, and optical properties of the synthesized films were analyzed using grazing incidence X-ray diffraction (GIXRD), energy-dispersive X-ray spectroscopy (EDS), scanning electron microscopy (SEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). X-ray diffraction confirmed the coexistence of both ZnS and ZnO phases, and showed that the proportion of the ZnS phase increases with rising sulfurization temperature. The preferred mechanism for ZnS phase formation is the reaction of ZnO with gaseous sulfur. The Raman spectra of both films sulfurized at 500 °C and 550 °C are nearly identical, displaying the characteristic peaks of ZnS and ZnO. Additionally, ZnS within the composite films is under tensile strain. SEM images reveal that the samples exhibit a highly uniform, homogeneous, and pore-free surface, while XPS confirms the chemical states of Zn, S, and O. These ZnS-ZnO composites exhibit superior structural and optical properties, making them a promising environmentally friendly alternative for buffer layers in chalcogenide solar cellsItem Heat transfer investigation near the onset of nucleate boiling on a single artificial nucleate site: Influence of the wall orientation(Elsevier, 2025) Kharkwal, Himanshi; Zamoum, Mohammed; Barthès, Magali; Lanzetta, François; Combeau, Hervé; Tadrist, LounèsStudying the transition from natural convection to nucleate boiling is crucial for both the efficiency and safety of thermal systems. Present study aims to investigate the heat transfer characteristics at the transition of the natural convection and the nucleate boiling regimes. An experimental setup has been designed and implemented to perform experiments with FC72 on flat heating wall that can be inclined from 0° to 180°. This was possible thanks to the development of a boiling meter mounted on a pivoting axis. This work provides new insights into local wall heat transfer behavior and nucleation dynamics under varying gravitational configurations, contributing novel data on single-site boiling physics. Intermittent behavior with typical heat transfer cycles is evidenced. Two criteria are found to control this intermittency; the wall temperature threshold for bubble nucleation and the heat flux threshold needed to sustain bubble emission. A single isolated bubble leads to a variation in the transfer coefficient. Changing inclination from 0° to 180° increases the heat transfer coefficient in the bubble emission regime from 263 to 489 W/(m2 °C) but decreases it in natural convection from 240 to 176 W/(m2 °C)Item High-gain UWB Fabry-Perot cavity antenna with dual-notched band for high-resolution imaging applications(Walter de Gruyter GmbH, 2025) Merabet, Imen; Rouabah, Khaled; Belazzoug, Massinissa; Braham Chaouche, Youcef; Denidni, Tayeb A.In this paper, we propose an ultra-wideband (UWB) Fabry–Perot cavity (FPC) antenna with dual-notch (DN) bands, utilizing a partially reflective surface (PRS) as a superstrate and an artificial magnetic conductor (AMC) reflector to support and enhance a DN band UWB antenna. The antenna components work synergistically to improve gain and provide directional radiation characteristics, while effectively mitigating interference from 5G and WLAN signals in urban environment. The proposed FPC design is executed in two main steps. First, a planar monopole UWB antenna is designed to operate within the frequency range of 2.69 GHz–12.27 GHz, incorporating a DN at 5G-3.5 GHz and 5 GHz WLAN bands through a single-slotted electromagnetic bandgap (EBG) unit-cell placed near the feedline. Second, a 5 × 5 array of AMC reflector elements and a PRS are strategically placed at specific distances from the UWB antenna to increase the gain. The resulting FPC structure was designed, optimized in HFSS, fabricated, and experimentally validated. Both measured and simulated results confirm that the proposed FPC structure achieves a peak gain of 10.21 dBi at 8.8 GHz, highlighting its potential to address challenges in meeting UWB application requirements, including Radar systems dedicated to high-resolution infrastructure monitoring and microwave medical imaging