Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Minqian Chen"'
Publikováno v:
Plant Methods, Vol 15, Iss 1, Pp 1-11 (2019)
Abstract Background Deep learning algorithms for automated plant identification need large quantities of precisely labelled images in order to produce reliable classification results. Here, we explore what kind of perspectives and their combinations
Externí odkaz:
https://doaj.org/article/59ff86f94b474be19fa98f968cb9ed91
Induction of embryogenic development in haploid microspore stem cells in droplet-based microfluidics
Autor:
Felix Richter, Minqian Chen, Patrick Schaub, Florian Wüst, Di Zhang, Steffen Schneider, G. Alexander Groß, Patrick Mäder, Oleksandr Dovzhenko, Klaus Palme, J. Michael Köhler, Jialan Cao
Publikováno v:
Lab on a chip. 22(22)
A microfluidic setup for consistent generation of droplets containing microspores was developed. Androgenesis and growth with final embryo formation can be induced. The system further enables dose–response studies, as shown with trichostatin A.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f3b0167bbbe7ebe9eb3c57c361316e5
https://pubmed.ncbi.nlm.nih.gov/36196753
https://pubmed.ncbi.nlm.nih.gov/36196753
Autor:
Sebastian Sachs, Rune Barnkob, Christian Cierpka, Minqian Chen, Patrick Mäder, Massimiliano Rossi
Publikováno v:
14th International Symposium on Particle Image Velocimetry. 1
Defocus methods have become more and more popular for the estimation of the 3D position of particles in flows (Cierpka and Kahler, 2011; Rossi and K ¨ ahler, 2014). Typically the depth positions of particles are ¨ determined by the defocused partic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a219fe05e19e47c637262063479f59b7
https://doi.org/10.18409/ispiv.v1i1.80
https://doi.org/10.18409/ispiv.v1i1.80
Publikováno v:
Physica B: Condensed Matter. 632:413700
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a838e31a768ae7811913e06730197135
https://doi.org/10.1016/j.physb.2022.413700
https://doi.org/10.1016/j.physb.2022.413700
Autor:
Christian Cierpka, Sebastian Sachs, Patrick Mäder, Minqian Chen, Massimiliano Rossi, Rune Barnkob
Publikováno v:
Measurement Science and Technology. 32:094011
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cda81588e490d03b5bc05363db281d02
https://doi.org/10.1088/1361-6501/abfef6
https://doi.org/10.1088/1361-6501/abfef6
Publikováno v:
Plant Methods
Plant Methods, Vol 15, Iss 1, Pp 1-11 (2019)
Plant Methods, Vol 15, Iss 1, Pp 1-11 (2019)
Background Deep learning algorithms for automated plant identification need large quantities of precisely labelled images in order to produce reliable classification results. Here, we explore what kind of perspectives and their combinations contain m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8d65c5128fdd4567600be4f20768423
http://europepmc.org/articles/PMC6651978
http://europepmc.org/articles/PMC6651978
Publikováno v:
Physica B: Condensed Matter. 602:412616
We design a four-quantum-dot system subjected to a time-dependent external field. The average current through the quantum dot system is obtained by using the method of non-equilibrium Green's function. By adjusting either the amplitude or frequency o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5613cb036b78e65d905f88fbf9710260
https://doi.org/10.1016/j.physb.2020.412616
https://doi.org/10.1016/j.physb.2020.412616
Publikováno v:
Journal of Advanced Transportation, Vol 2024 (2024)
The travel time reliability (TTR) is crucial for evaluating the reliability of road networks, but real traffic data is often incomplete and sparse. This study validates that road network TTR conforms to a normal distribution and devises a quantificat
Externí odkaz:
https://doaj.org/article/fcaf7fdbed734168ab7634c9dbe937bf
Publikováno v:
Measurement Science and Technology. 31:074015
Many applications in chemistry, biology and medicine use microfluidic devices to separate, detect and analyze samples on a miniaturized size-level. Fluid flows evolving in channels of only several tens to hundreds of micrometers in size are often of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ec2ac8fc43a2b9ff675642a185a092e
https://doi.org/10.1088/1361-6501/ab7bfd
https://doi.org/10.1088/1361-6501/ab7bfd