Výsledky vyhledávání

Akademický článek

Aalto Gear Fault datasets for deep-learning based diagnosisMendeley DataMendeley DataMendeley Data

Autor: Zacharias Dahl, Aleksanteri Hämäläinen, Aku Karhinen, Jesse Miettinen, Andre Böhme, Samuel Lillqvist, Sampo Haikonen, Raine Viitala

Publikováno v: Data in Brief, Vol 57, Iss , Pp 111171- (2024)

Accurate system health state prediction through deep learning requires extensive and varied data. However, real-world data scarcity poses a challenge for developing robust fault diagnosis models. This study introduces two extensive datasets, Aalto Sh

Externí odkaz: https://doaj.org/article/c2153d87c6e1449ea7ac070d3eb3ffbb

Zobrazit plný text záznamu

Akademický článek

Mesenchymal GDNF promotes intestinal enterochromaffin cell differentiation

Autor: Toni T. Lemmetyinen, Emma W. Viitala, Linnea Wartiovaara, Pekka Päivinen, Heikki T. Virtanen, Nalle Pentinmikko, Pekka Katajisto, Tomi P. Mäkelä, Timothy C. Wang, Jaan-Olle Andressoo, Saara Ollila

Publikováno v: iScience, Vol 27, Iss 12, Pp 111246- (2024)

Summary: Enteroendocrine cells (EECs) differentiate and mature to form functionally distinct populations upon migration along the intestinal crypt-villus axis, but how niche signals affect this process is poorly understood. Here, we identify expressi

Externí odkaz: https://doaj.org/article/ea27196119484f11b10254daaf73c7e0

Zobrazit plný text záznamu

Akademický článek

Linear growth pattern can be used to predict ascending aortic aneurysm growth.

Autor: Viitala, Iida-Mari^1,2 (AUTHOR) iida-mari.viitala@pshyvinvointialue.fi, Selander, Tuomas³ (AUTHOR), Hedman, Marja^1,4 (AUTHOR), Turtiainen, Johanna² (AUTHOR)

Publikováno v: Scandinavian Cardiovascular Journal. Dec2024, Vol. 58 Issue 1, p1-9. 9p.

Zobrazit plný text záznamu

Plný text ve formátu HTML