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	23221	UHPLC-Q Exactive-Orbitrap-MS and network pharmacology analyses to investigate the mechanism by which Danggui-Shaoyao-San affects 27-OHC-induced cell damage in SH-SY5Y/C6 coculture Enthalten in BMC complementary medicine and therapies Bd. 25, 24.2.2025, Nr. 1, date:12.2025: 1-20
	23222	ULODNet: A Unified Lane and Obstacle Detection Network Towards Drivable Area Understanding in Autonomous Navigation Enthalten in Journal of intelligent & robotic systems Bd. 105, 20.4.2022, Nr. 1, date:5.2022: 1-11
	23223	Ultra violet sensors based on nanostructured ZnO spheres in network of nanowires: a novel approach Enthalten in Nanoscale research letters Bd. 2, 3.3.2007, Nr. 3, date:3.2007: 161-167
	23224	Ultrahigh specificity in a network of computationally designed protein-interaction pairs Enthalten in Nature Communications Bd. 9, 11.12.2018, Nr. 1, date:12.2018: 1-13
	23225	Ultrasonic location of inner crack defects in a compound elastic cylinder using an artificial neural-network apparatus Enthalten in Russian journal of nondestructive testing Bd. 52, 7.6.2016, Nr. 3, date:3.2016: 119-124
	23226	Ultrasonic Testing of Corrosion in Aircraft Rivet Using Spiking Neural Network Enthalten in Journal of nondestructive evaluation Bd. 42, 29.8.2023, Nr. 3, date:9.2023: 1-11
	23227	Ultrasound-mediated blood–brain barrier opening uncovers an intracerebral perivenous fluid network in persons with Alzheimer’s disease Enthalten in Fluids and barriers of the CNS Bd. 20, 16.6.2023, Nr. 1, date:12.2023: 1-16
	23228	Umbilical Cord Blood-Derived Mononuclear Cells Exhibit Pericyte-Like Phenotype and Support Network Formation of Endothelial Progenitor Cells In Vitro Enthalten in Annals of biomedical engineering Bd. 43, 17.3.2015, Nr. 10, date:10.2015: 2552-2568
	23229	Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis Enthalten in Journal of neuro-oncology Bd. 166, 11.1.2024, Nr. 1, date:1.2024: 1-15
	23230	Uncertainties in neural network model based on carbon dioxide concentration for occupancy estimation Enthalten in Journal of mechanical science and technology Bd. 31, 20.5.2017, Nr. 5, date:5.2017: 2573-2580

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