Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Daniel Midtvedt"'
Autor:
Harshith Bachimanchi, Matthew I. M. Pinder, Chloé Robert, Pierre De Wit, Jonathan Havenhand, Alexandra Kinnby, Daniel Midtvedt, Erik Selander, Giovanni Volpe
Publikováno v:
Limnology and Oceanography Letters, Vol 9, Iss 4, Pp 324-339 (2024)
ABSTRACT The implementation of deep learning algorithms has brought new perspectives to plankton ecology. Emerging as an alternative approach to established methods, deep learning offers objective schemes to investigate plankton organisms in diverse
Externí odkaz:
https://doaj.org/article/90849ce8678f4405902f6993e60a8dd2
Autor:
David Tomeček, Henrik Klein Moberg, Sara Nilsson, Athanasios Theodoridis, Iwan Darmadi, Daniel Midtvedt, Giovanni Volpe, Olof Andersson, Christoph Langhammer
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Environmental humidity variations are ubiquitous and high humidity characterizes fuel cell and electrolyzer operation conditions. Since hydrogen-air mixtures are highly flammable, humidity tolerant H2 sensors are important from safety and pr
Externí odkaz:
https://doaj.org/article/baf1e71228f9401c80300d3626074abc
Autor:
Benjamin Midtvedt, Jesús Pineda, Fredrik Skärberg, Erik Olsén, Harshith Bachimanchi, Emelie Wesén, Elin K. Esbjörner, Erik Selander, Fredrik Höök, Daniel Midtvedt, Giovanni Volpe
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
Object detection using machine learning universally requires vast amounts of training datasets. Midtvedt et al. proposes a deep-learning method that enables detecting microscopic objects with sub-pixel accuracy from a single unlabeled image by exploi
Externí odkaz:
https://doaj.org/article/725fdbe65ba74b758eb43c1f4b9ab5ae
Publikováno v:
eLife, Vol 11 (2022)
The marine microbial food web plays a central role in the global carbon cycle. However, our mechanistic understanding of the ocean is biased toward its larger constituents, while rates and biomass fluxes in the microbial food web are mainly inferred
Externí odkaz:
https://doaj.org/article/30301e09066e448f9a8c4f193cd38fd3
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-9 (2019)
Label-free, spatio-temporal imaging of cellular physiological responses is challenging. Here the authors combine digital holographic microscopy with a millifluidic chip and mathematical modelling to quantify cell volume, mass and cell uptake under ch
Externí odkaz:
https://doaj.org/article/7beea7bfef8044bd83a66a1ec7e086bb
Autor:
Shada Abuhattum, Kyoohyun Kim, Titus M. Franzmann, Anne Eßlinger, Daniel Midtvedt, Raimund Schlüßler, Stephanie Möllmert, Hui-Shun Kuan, Simon Alberti, Vasily Zaburdaev, Jochen Guck
Publikováno v:
Frontiers in Physics, Vol 6 (2018)
Many organisms, including yeast cells, bacteria, nematodes, and tardigrades, endure harsh environmental conditions, such as nutrient scarcity, or lack of water and energy for a remarkably long time. The rescue programs that these organisms launch upo
Externí odkaz:
https://doaj.org/article/5b14626c1aba4cfab0151420966c937b
Autor:
Matthias Christoph Munder, Daniel Midtvedt, Titus Franzmann, Elisabeth Nüske, Oliver Otto, Maik Herbig, Elke Ulbricht, Paul Müller, Anna Taubenberger, Shovamayee Maharana, Liliana Malinovska, Doris Richter, Jochen Guck, Vasily Zaburdaev, Simon Alberti
Publikováno v:
eLife, Vol 5 (2016)
Cells can enter into a dormant state when faced with unfavorable conditions. However, how cells enter into and recover from this state is still poorly understood. Here, we study dormancy in different eukaryotic organisms and find it to be associated
Externí odkaz:
https://doaj.org/article/7c42b601ed0f4215b28b9dbe9023c640
Autor:
Jesús Pineda, Benjamin Midtvedt, Harshith Bachimanchi, Sergio Noé, Daniel Midtvedt, Giovanni Volpe, Carlo Manzo
Publikováno v:
Nature Machine Intelligence. 5:71-82
The characterization of dynamical processes in living systems provides important clues for their mechanistic interpretation and link to biological functions. Owing to recent advances in microscopy techniques, it is now possible to routinely record th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34a30f720a1a699277d924bf06e965b7
https://doi.org/10.1038/s42256-022-00595-0
https://doi.org/10.1038/s42256-022-00595-0
Autor:
Daniel Midtvedt, Vasilii Mylnikov, Alexander Stilgoe, Mikael Käll, Halina Rubinsztein-Dunlop, Giovanni Volpe
Publikováno v:
Nanophotonics. 11:3189-3214
The deep-learning revolution is providing enticing new opportunities to manipulate and harness light at all scales. By building models of light–matter interactions from large experimental or simulated datasets, deep learning has already improved th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3ef7fee8fa571299611c9158742c8d1
https://doi.org/10.1515/nanoph-2022-0197
https://doi.org/10.1515/nanoph-2022-0197
Autor:
Barbora Špačková, Henrik Klein Moberg, Joachim Fritzsche, Johan Tenghamn, Gustaf Sjösten, Hana Šípová-Jungová, David Albinsson, Quentin Lubart, Daniel van Leeuwen, Fredrik Westerlund, Daniel Midtvedt, Elin K. Esbjörner, Mikael Käll, Giovanni Volpe, Christoph Langhammer
Publikováno v:
Nature Methods. 19:751-758
Label-free characterization of single biomolecules aims to complement fluorescence microscopy in situations where labeling compromises data interpretation, is technically challenging or even impossible. However, existing methods require the investiga
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ab169a7115bc081e90789464fffb2a
https://doi.org/10.1038/s41592-022-01491-6
https://doi.org/10.1038/s41592-022-01491-6