Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Yuval Sade"'
Autor:
Avishai Maliah, Nadine Santana-Magal, Shivang Parikh, Sagi Gordon, Keren Reshef, Yuval Sade, Aseel Khateeb, Alon Richter, Amit Gutwillig, Roma Parikh, Tamar Golan, Matan Krissi, Manho Na, Gal Binshtok, Paulee Manich, Nadav Elkoshi, Sharon Grisaru-Tal, Valentina Zemser-Werner, Ronen Brenner, Hananya Vaknine, Eran Nizri, Lilach Moyal, Iris Amitay-Laish, Luiza Rosemberg, Ariel Munitz, Noga Kronfeld-Schor, Eric Shifrut, Oren Kobiler, Asaf Madi, Tamar Geiger, Yaron Carmi, Carmit Levy
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract T cell inhibitory mechanisms prevent autoimmune reactions, while cancer immunotherapy aims to remove these inhibitory signals. Chronic ultraviolet (UV) exposure attenuates autoimmunity through promotion of poorly understood immune-suppressiv
Externí odkaz:
https://doaj.org/article/558f6188a6ba4158b35fee08d311324d
Autor:
Yuval Sadeh, Xuan Zhu, David Dunkerley, Jeffrey P. Walker, Yuxi Zhang, Offer Rozenstein, V.S. Manivasagam, Karine Chenu
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 96, Iss , Pp 102260- (2021)
The dynamics of Leaf Area Index (LAI) from space is key to identify crop types and their phenology over large areas, and to characterize spatial variations within growers’ fields. However, for years remote-sensing applications have been constrained
Externí odkaz:
https://doaj.org/article/eee093ace722404496b276d520b1bd6f
Publikováno v:
Remote Sensing, Vol 14, Iss 1, p 65 (2021)
Optimised farm crop productivity requires careful management in response to the spatial and temporal variability of yield. Accordingly, combination of crop simulation models and remote sensing data provides a pathway for providing the spatially varia
Externí odkaz:
https://doaj.org/article/035d69db96aa4ab087435799ae229476
Publikováno v:
Remote Sensing, Vol 13, Iss 12, p 2395 (2021)
Spatial information embedded in a crop model can improve yield prediction. Leaf area index (LAI) is a well-known crop variable often estimated from remote-sensing data and used as an input into crop models. In this study, we evaluated the assimilatio
Externí odkaz:
https://doaj.org/article/8dc27be8d195414987e873d89ca20b62
Publikováno v:
Remote Sensing, Vol 10, Iss 10, p 1505 (2018)
The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-
Externí odkaz:
https://doaj.org/article/2646a189e5da4a118c87ad44c80f3fee