Results 181 to 190 of about 679,610 (316)

A Low-Cycle Fatigue Life Prediction Method for a Drive Shaft Considering the Effects of Loading and Strength Degradation. [PDF]

Materials (Basel)
Yang L, Yu X, Liu F, Wang L, Zhang J, Zhang X, Zhang J.   +6 more
europepmc   +1 more source

Promiscuous stimulation of HSP70 ATPase activity by parasite‐derived J‐domains

FEBS Open Bio, EarlyView.
The malaria parasite Plasmodium falciparum exports three highly homologous yet functionally divergent J‐domain proteins into human erythrocytes. Here, we show that J‐domains isolated from all three proteins effectively stimulate the ATPase activity of both endogenous host and exported parasite HSP70 chaperones.
Julian Barth, Moritz Koch, Le‐Han Rössner, Johanna Eichhorn, Denys Pogoryelov, Matthias P. Mayer, Jude M. Przyborski   +6 more
wiley   +1 more source

Crack propagation mechanism and life prediction of liner under thermal fatigue loads. [PDF]

Sci Rep
Wang X, Li W, Zheng M, Zeng Q, Li Y, Yang H, Wang C.   +6 more
europepmc   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

A deep learning framework for remaining useful life prediction of turbofan engines with partial sensor failure. [PDF]

PLoS One
Tang D.
europepmc   +1 more source

Chameleon sequences reveal structural effects in proteins representing micelle‐like distribution of hydrophobicity

FEBS Open Bio, EarlyView.
Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman, Katarzyna Stapor, Leszek Konieczny, Krzysztof Gądek, Piotr Nowakowski   +4 more
wiley   +1 more source

Physics-Informed Monotonic Conformer for Remaining Useful Life Prediction of Hydraulic Systems. [PDF]

Sensors (Basel)
He X, Zhang C, Wang J, Zhao X, Yao J, Lu C, Yang X.   +6 more
europepmc   +1 more source

Exon 7 splicing of ERα predicts poor prognosis and increases phenotypic heterogeneity in luminal a subtype breast cancer

FEBS Open Bio, EarlyView.
ERα splice variant ERα∆7 lacks the C‐terminus, and its expression may change phenotypes of breast cancers. Our results showed that ERα∆7 is found in the luminal A subtype, and elevated ERα∆7 levels are linked to improved cell survival with lower proliferation and migration.
Long Wai Tsui, Taobo Hu, Thomson Christian Husein, Wai Hei Shek, Bingrong Chen, Depeng Wang, Shu Wang, Weichuan Yu, Xiaodan Fan, Mengping Long, Toyotaka Ishibashi   +10 more
wiley   +1 more source

CoPAL: Conformal Prediction for Active Learning with Application to Remaining Useful Life Estimation in Predictive Maintenance

Active learning has received considerable attention as an approach to obtain high predictive performance while minimizing the labeling effort. A central component of the active learning framework concerns the selection of objects for labeling, which are ...
Magnússon, Sindri,, Boström, Henrik,, Kharazian, Zahra,, Lindgren, Tony,   +3 more
core  

Shelf-Life Prediction of Shrimp Gravlax Using Machine Learning: Integrating Traditional Processing with AI Modeling. [PDF]

Foods
Emir Coban O, Kilincer IF, Jamshidi A, Coban MZ.   +3 more
europepmc   +1 more source