@article{MTMT:36413939,
	title = {Phytochemistry diversity and antioxidant activities of Cladostephus spongiosus (Hudson) C. Agardh},
	url = {https://m2.mtmt.hu/api/publication/36413939},
	author = {Aalilou, Youssra and Hassoun, Mustapha and Moussa, Hanaa and Zengin, Gokhan and Ak, Güneş and Ullah, Riaz and Alotaibi, Amal and Bouyahya, Abdelhakim and Faouzi, My El Abbes},
	doi = {10.1016/j.bse.2025.105160},
	journal-iso = {BIOCHEM SYST ECOL},
	journal = {BIOCHEMICAL SYSTEMATICS AND ECOLOGY},
	volume = {124},
	unique-id = {36413939},
	issn = {0305-1978},
	year = {2026},
	eissn = {1873-2925},
	pages = {105160}
}

@article{MTMT:36528929,
	title = {Impact of blending alcohols, ethers and ketones with TPRF mixtures on smoke point: an experimental and neural network analysis},
	url = {https://m2.mtmt.hu/api/publication/36528929},
	author = {Abakar, Ruaa Ala Eldin Ageeb and Jameel, Abdul Gani Abdul},
	doi = {10.1016/j.fuel.2025.136855},
	journal-iso = {FUEL},
	journal = {FUEL},
	volume = {406},
	unique-id = {36528929},
	issn = {0016-2361},
	keywords = {oxygenates; Smoke point; TPRF; ANN, ETR, SVR},
	year = {2026},
	eissn = {1873-7153}
}

@article{MTMT:36508977,
	title = {Corrosion Inhibition of Monel 400 in 1M HCl Using a Novel Eco Inhibitor Curcumin and Bis Curcumin Bis Azodye},
	url = {https://m2.mtmt.hu/api/publication/36508977},
	author = {Abbas, Mahmoud and Abd El-Aal, Reda M. and Beshta, Amira M. and Abbas, Dalia M.},
	doi = {10.21608/ejchem.2025.404494.12051},
	journal-iso = {EGYPT J CHEM},
	journal = {EGYPTIAN JOURNAL OF CHEMISTRY},
	volume = {69},
	unique-id = {36508977},
	issn = {0449-2285},
	keywords = {CURCUMIN; Electrochemical; Azodye; Monel 400},
	year = {2026},
	eissn = {2357-0245},
	pages = {161-178}
}

@article{MTMT:36519571,
	title = {Simultaneous rational number codes: Decoding beyond half the minimum distance with multiplicities and bad primes},
	url = {https://m2.mtmt.hu/api/publication/36519571},
	author = {Abbondati, Matteo and Guerrini, Eleonora and Lebreton, Romain},
	doi = {10.1016/j.jsc.2025.102481},
	journal-iso = {J SYMB COMPUT},
	journal = {JOURNAL OF SYMBOLIC COMPUTATION},
	volume = {132},
	unique-id = {36519571},
	issn = {0747-7171},
	keywords = {error correction; Primes of bad reduction; Failure probability analysis; Simultaneous rational reconstruction; Hybrid error model; Beyond unique decoding},
	year = {2026},
	eissn = {1095-855X}
}

@article{MTMT:36443275,
	title = {HyOCNN: Hybrid-optimized convolutional neural network for robust image classification},
	url = {https://m2.mtmt.hu/api/publication/36443275},
	author = {Abdalla, Karmand Hussein and Daneshfar, Fatemeh and Hosseini, Eghbal and Oussalah, Mourad},
	doi = {10.1016/j.bspc.2025.109040},
	journal-iso = {BIOMED SIGNAL PROCES},
	journal = {BIOMEDICAL SIGNAL PROCESSING AND CONTROL},
	volume = {113},
	unique-id = {36443275},
	issn = {1746-8094},
	year = {2026},
	eissn = {1746-8108},
	pages = {109040},
	orcid-numbers = {Abdalla, Karmand Hussein/0000-0001-8552-3158; Daneshfar, Fatemeh/0000-0003-3150-3527; Oussalah, Mourad/0000-0002-4422-8723}
}

@article{MTMT:36507534,
	title = {Ab initio study of N2V color center in lonsdaleite/diamond dual structure: A two-site Hubbard model},
	url = {https://m2.mtmt.hu/api/publication/36507534},
	author = {Abdelghafar, KA. and Choi, DS. and Askar, K},
	doi = {10.1016/j.commatsci.2025.114412},
	journal-iso = {COMP MATER SCI},
	journal = {COMPUTATIONAL MATERIALS SCIENCE},
	volume = {263},
	unique-id = {36507534},
	issn = {0927-0256},
	year = {2026},
	eissn = {1879-0801}
}

@article{MTMT:36468332,
	title = {Emerging role and interplay of programmed cell death in endometritis: Insights into mechanisms and therapeutic targets},
	url = {https://m2.mtmt.hu/api/publication/36468332},
	author = {Abdelmawgood, Islam Ahmed and Kotb, Dina M. M. and Mostafa, Ahmed Ezzat and Sharaf, Bahaa and Ramadan, Sohaib Ali and Isamil, Seif and Moataz, Ali and Abdelghany, Mariam and Hussien, Donia Mohamed and Boushra, Michael Ibrahim},
	doi = {10.1016/j.repbio.2025.101098},
	journal-iso = {REPROD BIOL},
	journal = {REPRODUCTIVE BIOLOGY},
	volume = {26},
	unique-id = {36468332},
	issn = {1642-431X},
	abstract = {Endometritis is the inflammation of the endometrial lining, frequently linked to pelvic pain. Endometritis is significantly associated with postpartum problems, including infertility. Programmed cell death (PCD) is a genetically regulated mechanism of autonomic and regulated cell death that preserves homeostasis and promotes development. PCD, which includes apoptosis, pyroptosis, autophagy, ferroptosis, and necroptosis, is essential in the pathogenesis of reproductive diseases, including endometritis. Despite the limited study on PCD in endometritis, it is essential to identify important molecules and comprehend their regulatory functions for effective disease prevention and management. This review delineates the different types of PCD and their interactions in endometritis. It also evaluates the progress in PCD research pertaining to endometritis. The objective is to create a basis for subsequent investigations into the function and interaction of PCD in endometritis. We anticipate that this study will facilitate the exploration of novel PCD targets for endometritis treatment, hence encouraging comprehensive research.},
	keywords = {APOPTOSIS; APOPTOSIS; MICE DEFICIENT; Endometritis; ENDOPLASMIC-RETICULUM STRESS; Autophagy; ANTIBIOTIC-TREATMENT; NEUTROPHIL EXTRACELLULAR TRAPS; Pyroptosis; Ferroptosis; NLRP3 INFLAMMASOME; Oxidative stress; TXNIP/NLRP3 INFLAMMASOME ACTIVATION},
	year = {2026},
	eissn = {2300-732X}
}

@article{MTMT:36439253,
	title = {Wavelet-based hybrid CNN-BiLSTM approach in tool wear monitoring},
	url = {https://m2.mtmt.hu/api/publication/36439253},
	author = {Abdeltawab, Ahmed and Xi, Zhang and Longjia, Zhang and Galal, Ahmed M.},
	doi = {10.1016/j.dsp.2025.105529},
	journal-iso = {DIGIT SIGNAL PROCESS},
	journal = {DIGITAL SIGNAL PROCESSING},
	volume = {168},
	unique-id = {36439253},
	issn = {1051-2004},
	abstract = {Recent advancements in deep learning techniques have revolutionized modeling from raw sensor data, leading to more challenges in tool wear monitoring. An effective tool wear monitoring model ensures reliable and efficient manufacturing processes. This work presents a novel approach that combines wavelet transform techniques for multiresolution analysis with a hybrid deep learning method for tool wear identification. The proposed model incorporates the Maximal Overlap Discrete Wavelet Transform (MODWT) for raw signal preprocessing, paired with a hybrid deep learning architecture that combines CNNs and BiLSTM. First, to identify the most significant information related to tool condition, the energy distribution across each MODWT decomposition level is analyzed. Higher decomposition levels play a critical role in capturing the cutting signal's medium- and low-frequency components, which are crucial for detecting significant changes in the tool wear progression. Then, the effectiveness of the proposed model was evaluated and compared to other widely used deep learning models using milling datasets. The results show that the MODWT-CNN-BiLSTM model consistently outperforms other models in terms of key performance metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and regression coefficient (R-2) across all datasets. Specifically, the proposed model achieved the lowest MAE (0.0197) and RMSE (0.0276), along with the highest R-2 value (0.9839), demonstrating superior accuracy and reliability. This approach underscores the effectiveness of combining wavelet-based analysis, such as MODWT, with deep learning techniques like CNNs and BiLSTM for tool wear monitoring in practical milling operations.},
	keywords = {prediction; Signal processing; SIGNALS; Milling process; TRANSFORM; wavelet transform; TOOL WEAR},
	year = {2026},
	eissn = {1095-4333}
}

@article{MTMT:36267405,
	title = {Cubic Trigonometric Triangular Spline with Rational Basis Functions in 3-Dimensional Space},
	url = {https://m2.mtmt.hu/api/publication/36267405},
	author = {Abd, Halim Muhammad Syawal and Hadi, Normi Abdul and Nayan, Asmahani and Varlamova, Lyudmila},
	doi = {10.37934/araset.56.2.7490},
	journal-iso = {JOURNAL OF ADVANCED RESEARCH IN APPLIED SCIENCES AND ENGINEERING TECHNOLOGY},
	journal = {JOURNAL OF ADVANCED RESEARCH IN APPLIED SCIENCES AND ENGINEERING TECHNOLOGY},
	volume = {56},
	unique-id = {36267405},
	issn = {2462-1943},
	year = {2026},
	pages = {74-90}
}

@article{MTMT:36512892,
	title = {Comparison of power generation from high-potential geothermal fields of Iran: Thermodynamic and exergoeconomic assessment of different configurations},
	url = {https://m2.mtmt.hu/api/publication/36512892},
	author = {Abdolalipouradl, Mehran and Namkhah, Mohammad and Mohammadkhani, Farzad and Yari, Mortaza},
	doi = {10.1016/j.applthermaleng.2025.128769},
	journal-iso = {APPL THERM ENG},
	journal = {APPLIED THERMAL ENGINEERING},
	volume = {282},
	unique-id = {36512892},
	issn = {1359-4311},
	keywords = {Iran; Organic Rankine Cycle; Geothermal power plant; Flash cycle; Exergoeconomic optimization},
	year = {2026},
	eissn = {1873-5606}
}