Výsledky vyhledávání - "Stefan Heinen"

Akademický článek

On Noise-Sensitive Automatic Tuning of Gate-Defined Sensor Dots

Autor: Fabian Hader, Jan Vogelbruch, Simon Humpohl, Tobias Hangleiter, Chimezie Eguzo, Stefan Heinen, Stefanie Meyer, Stefan van Waasen

Publikováno v: IEEE Transactions on Quantum Engineering, Vol 4, Pp 1-18 (2023)

In gate-defined quantum dot systems, the conductance change of electrostatically coupled sensor dots allows the observation of the quantum dots' charge and spin states. Therefore, the sensor dot must be optimally sensitive to changes in its electrost

Externí odkaz: https://doaj.org/article/a31169224b9240bbb7649bae5276a6a2

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Akademický článek

An Integrated 50 V Boost Controller With Digitally-Assisted MPPT for Submodule PV Applications

Autor: Michael Hanhart, Leon Weihs, Leo Rolff, Jonas Zoche, Jan Grobe, Ralf Wunderlich, Stefan Heinen

Publikováno v: IEEE Open Journal of Power Electronics, Vol 4, Pp 221-236 (2023)

This work introduces an integrated maximum power point tracking boost controller for photovoltaic submodule applications. The IC offers a wide input voltage range from 7 V to 24 V, whereas the output voltage is actively limited to 50 V. The presented

Externí odkaz: https://doaj.org/article/1e9fc08d1f5e4af69858a1acc6adc6f5

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Akademický článek

Reducing training data needs with minimal multilevel machine learning (M3L)

Autor: Stefan Heinen, Danish Khan, Guido Falk von Rudorff, Konstantin Karandashev, Daniel Jose Arismendi Arrieta, Alastair J A Price, Surajit Nandi, Arghya Bhowmik, Kersti Hermansson, O Anatole von Lilienfeld

Publikováno v: Machine Learning: Science and Technology, Vol 5, Iss 2, p 025058 (2024)

For many machine learning applications in science, data acquisition, not training, is the bottleneck even when avoiding experiments and relying on computation and simulation. Correspondingly, and in order to reduce cost and carbon footprint, training

Externí odkaz: https://doaj.org/article/0506d6d035634242bde078321393b2b8

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Akademický článek

Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials

Autor: Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld

Publikováno v: Machine Learning: Science and Technology, Vol 5, Iss 1, p 015052 (2024)

We present an automated data-collection pipeline involving a convolutional neural network and a large language model to extract user-specified tabular data from peer-reviewed literature. The pipeline is applied to 74 reports published between 1957 an

Externí odkaz: https://doaj.org/article/95be18147f884c3e90f822b66fe4feae

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Akademický článek

Transgene distribution and immune response after ultrasound delivery of rAAV9 and PHP.B to the brain in a mouse model of amyloidosis

Autor: Rikke Hahn Kofoed, Stefan Heinen, Joseph Silburt, Sonam Dubey, Chinaza Lilian Dibia, Miriam Maes, Elizabeth M. Simpson, Kullervo Hynynen, Isabelle Aubert

Publikováno v: Molecular Therapy: Methods & Clinical Development, Vol 23, Iss , Pp 390-405 (2021)

Efficient disease-modifying treatments for Alzheimer disease, the most common form of dementia, have yet to be established. Gene therapy has the potential to provide the long-term production of therapeutic in the brain following a single administrati

Externí odkaz: https://doaj.org/article/2fac79d9eff6473f8934f1dbcffeddbc

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Akademický článek

Deletion of complement factor H-related genes CFHR1 and CFHR3 is associated with atypical hemolytic uremic syndrome.

Autor: Peter F Zipfel, Matthew Edey, Stefan Heinen, Mihály Józsi, Heiko Richter, Joachim Misselwitz, Bernd Hoppe, Danny Routledge, Lisa Strain, Anne E Hughes, Judith A Goodship, Christoph Licht, Timothy H J Goodship, Christine Skerka

Publikováno v: PLoS Genetics, Vol 3, Iss 3, p e41 (2007)

Atypical hemolytic uremic syndrome (aHUS) is associated with defective complement regulation. Disease-associated mutations have been described in the genes encoding the complement regulators complement factor H, membrane cofactor protein, factor B, a

Externí odkaz: https://doaj.org/article/5dbab60a997e4d30ae0bf040891b6ada

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