Results 61 to 70 of about 239,815 (291)

Prediction of power grid fault repair time based on multi-model fusion

Dianxin kexue, 2020
There are many types of power grid faults,and the reasons are complicated.The prediction of fault repair time is difficult.Due to the rise of new technologies such as deep learning,it is feasible to accurately mine the faulty worksheet and accurately ...
Jianyue PAN, Yizhen WU, Hanlin XU
doaj   +2 more sources

PT-Informer: A Deep Learning Framework for Nuclear Steam Turbine Fault Diagnosis and Prediction

Machines, 2023
The health status of equipment is of paramount importance during the operation of nuclear power plants. The occurrence of faults not only leads to significant economic losses but also poses risks of casualties and even major accidents, with unimaginable ...
Jiajing Zhou, Zhao An, Zhile Yang, Yanhui Zhang, Huanlin Chen, Weihua Chen, Yalin Luo, Yuanjun Guo   +7 more
doaj   +1 more source

Transferrin receptor 1‐mediated iron uptake supports thermogenic activation in human cervical‐derived adipocytes

FEBS Letters, EarlyView.
In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai, Mizuki Seo, Gyath Karadsheh, Fachrur Rizal Mahendra, Máté Á Demény, Ferenc Győry, János András Mótyán, László Fésüs, Endre Kristóf, Rini Arianti   +9 more
wiley   +1 more source

Prediction of zero crossing point of fault current based on Bayesian estimation

Zhejiang dianli, 2022
Breaking capacity of circuit breakers can no longer meet the continuous rising demand of fault current in present new power systems. The phrase-controlled fault interruption technology based on zero crossing point prediction is an important solution ...
LIU Yunfei, ZHOU Qiwen, FANG Taixun
doaj   +1 more source

Power system fault prediction using artificial neural networks [PDF]

, 1996
The medium term goal of the research reported in this paper was the development of a major in-house suite of strategic computer aided network simulation and decision support tools to improve the management of power systems.
Ryan, H. M., Tindle, J., Wong, K. C. P.
core  

Calpain small subunit homodimerization is robust and calcium‐independent

FEBS Letters, EarlyView.
Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy, Trina Dykstra‐MacPherson, Mathias A. Bell, Peter L. Davies, Ruby May A. Sullan   +4 more
wiley   +1 more source

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

FEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel, Carl P. O. Helmer, Shani Zev, Ronja Driller, Emily Buhr, Markus Reinbold, Renana Schwartz, Gabriel Foley, Mikael Boden, Daniel Garbe, Gerhard Schenk, Dan Thomas Major, Bernhard Loll, Thomas Brück   +13 more
wiley   +1 more source

Data-driven Soft Sensors in the Process Industry [PDF]

, 2009
In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control.
Abdi, Alhoniemi, Angelov, Angelov, Angelov, Arazo-Bravo, Atkeson, Bastin, Bauer, Bishop, Bogdan Gabrys, Bonne, Breiman, Bro, Casali, Chen, Chen, Chen, Chen, Chen, Choi, Chruy, Davies, Dayal, De Wolf, Desai, Devogelaere, Ding, Dong, Dong, Dote, Doyle, Dunia, Dunia, Dunia, Eriksson, Fellner, Fortuna, Fortuna, Frank, Freund, Funahashi, Gabrielsson, Gabrys, Gabrys, Gabrys, Gabrys, Gama, Geladi, Gomez, Gonzalez, Gonzalez, Goodwin, Gosset, Guyon, Han, Hastie, He, Hodge, Hotelling, Jackson, James, Jang, Jiang, Jolliffe, Jordaan, Jos de Assis, Kadlec, Kadlec, Kalos, Kampjarvi, Kittler, Kohavi, Kohonen, Kordon, Kourti, Kourti, Krogh, Kuncheva, Lee, Lee, Lee, Lee, Li, Li, Lin, Lin, Luo, Macias, Mandic, Marjanovic, Meleiro, Menold, Nauck, Neogi, Nomikos, Nomikos, Nomikos, Opitz, Park, Pearson, Pearson, Petr Kadlec, Poggio, Prasad, Principe, Qin, Qin, Qin, Qin, Radhakrishnan, Rnnar, Rong, Rotem, Ruta, Ruta, Schafer, Scheffer, Serneels, Sibylle Strandt, Stanimirova, Su, Tzanakou, van Sprang, van Sprang, Vapnik, Venkatasubramanian, Venkatasubramanian, Venkatasubramanian, Vilalta, Walczak, Walczak, Walczak, Wang, Wang, Wang, Wang, Warne, Weiss, Widmer, Wold, Wold, Wold, Wolpert, Yan, Yang, Zadeh, Zamprogna, Zamprogna, Zhang   +149 more
core   +1 more source

Diversity and complexity in neural organoids

FEBS Letters, EarlyView.
Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley   +1 more source

The neural crest‐associated gene ERRFI1 is involved in melanoma progression and resistance toward targeted therapy

Molecular Oncology, EarlyView.
ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang, Qian Sun, Daniel Novak, Lei Zhu, Juliane Poelchen, Tamara Steinfass, Yiman Wang, Viktor Umansky, Jochen Utikal   +8 more
wiley   +1 more source