Results 231 to 240 of about 705,347 (360)
Ouverture des châsses des saints Domitien & Mengold au Trésor de Notre-Dame de Huy
, 1982 Philippe George, christine charlier
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Direct Evidence of Topological Dirac Fermions in a Low Carrier Density Correlated 5d Oxide
Advanced Functional Materials, EarlyView.The 5d oxide BiRe2O6 is discovered as a low‐carrier‐density topological semimetal hosting symmetry‐protected Dirac fermions stabilized by nonsymmorphic symmetries. Angle‐resolved photoemission spectroscopy, quantum oscillations, and magnetotransport measurements reveal gapless Dirac cones, quasi‐2D Fermi surfaces, high carrier mobility, and a field ...
Premakumar Yanda +11 more
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BK and JC polyomavirus co-infection resulting in polyomavirus nephropathy and progressive multifocal leukoencephalopathy at the same time, a case report. [PDF]
Braz J Infect DisBriol S +5 more
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On Saint-Venant's principle in plane anisotropic elasticity
, 1972 Cornelius O. Horgan
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Fermi Surface Nesting and Anomalous Hall Effect in Magnetically Frustrated Mn2PdIn
Advanced Functional Materials, EarlyView.Mn2PdIn, a frustrated inverse Heusler alloy, showing electronic‐structure driven anomalous Hall effect with Weyl crossings, Fermi‐surface nesting and near‐zero magnetization ideal for low‐magnetization spintronics. Abstract Noncollinear magnets with near‐zero net magnetization and nontrivial bulk electronic topology hold significant promise for ...
Afsar Ahmed +7 more
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Advanced Functional Materials, EarlyView.Non‐covalent protein–protein interactions mediated by SH3, PDZ, or GBD domains enable the self‐assembly of stable and biocatalytically active hydrogel materials. These soft materials can be processed into monodisperse foams that, once dried, exhibit enhanced mechanical stability and activity and are easily integrated into microstructured flow ...
Julian S. Hertel +5 more
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Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Etude de la contamination de pectinidés (coquilles Saint-Jacques et pétoncles) par le cadmium, le mercure et le plomb dans quelques zones de pêche françaises [PDF]
, 2010 Teba Gil-Díaz +3 more
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