Results 51 to 60 of about 803,101 (318)

Probability of Hesitant Fuzzy Event and Hesitant Fuzzy Probability Reasoning Method [PDF]

Jisuanji gongcheng, 2018
In order to quantify the uncertainty of the occurrence of hesitant fuzzy event in random experiment,the probability of hesitant fuzzy event is defined combining fuzzy probability theory and hesitant fuzzy set theory.The definition of conditional ...
LI Jiang,YUAN Xiujiu,ZHAO Xuejun
doaj   +1 more source

Mitochondrial Calcium Uniporter Drives Chemoresistance in Pancreatic Cancer via Glutathione‐Mediated Stemness Maintenance

Advanced Science, EarlyView.
PDAC has a poor prognosis due to chemoresistance. We revealed that MCU upregulation is associated with chemoresistance and stemness in PDAC. MCU‐mediated Ca2+ influx induced ER stress, activating the PERK‐ATF4/NRF2 axis to enhance PSAT1/SLC711 expression and glutathione synthesis, reducing ROS and maintaining stemness.
Zekun Li, Chenyang Meng, Guangcong Shen, Yueying Shan, Junjin Wang, Diliyaer Abudukeremu, Rui Zhao, Bo Ni, Chao Xu, Xiaofan Guo, Jun Yu, Kaiyuan Wang, Shengyu Yang, YunZhan Li, Yongjie Xie, Tianxing Zhou, Jihui Hao, Xiuchao Wang   +17 more
wiley   +1 more source

Global Sensitivity Analysis of Fuzzy Distribution Parameter on Failure Probability and Its Single-Loop Estimation

Journal of Applied Mathematics, 2014
An extending Borgonovo’s global sensitivity analysis is proposed to measure the influence of fuzzy distribution parameters on fuzzy failure probability by averaging the shift between the membership functions (MFs) of unconditional and conditional failure
Lei Cheng, Zhenzhou Lu, Luyi Li
doaj   +1 more source

Specification of the Conditional Expectation by Simple Linear Regression Model For Binomial Distribution Conditioned with Varying Sample Size. [PDF]

المجلة العراقية للعلوم الاحصائية, 2009
In this research, we consider the study of conditional expectation and it's relationship with regression model. The conditional expectation has a linear form which is specified as a simple linear regression model. The power transformation was used on the
doaj   +1 more source

Data‐Driven Fatigue Prediction of Superalloys: A Novel Strategy Integrating Transfer Learning and Partial Label Learning for Addressing Ambiguous Data

Advanced Science, EarlyView.
A novel machine learning strategy tackles ambiguous compositional data to predict superalloy fatigue. By integrating partial label with transfer learning and enriching features through thermodynamic calculations, this approach achieves superior accuracy and interpretability.
Haopeng Lv, Jiawei Yin, Dayong Wu, Ziyuan Rao, Chao Su, Jie Kang, Qian Wang, Haikun Ma, Huicong Dong, Yandong Wang, Ru Su   +10 more
wiley   +1 more source

AN ALTERNATIVE CONCEPT OF FUZZY FUNCTIONAL DEPENDENCY BY USING CONDITIONAL PROBABILITY

Jurnal Informatika, 2001
This paper proposes an alternative concept of Fuzzy Functional Dependency (FFD) based on the theory of conditional probability. We examine some properties of conditional probability and its relation with fuzzy sets.
Rolly Intan
doaj  

Methodology for assessing probability of extreme hydrologic events coincidence [PDF]

Facta Universitatis. Series: Architecture and Civil Engineering, 2010
The aim of the presented research is improvement of methodology for probability calculation of coinciding occurrence of historic floods and droughts in the same year.
Prohaska Stevan, Blagojević Borislava, Ilić Aleksandra   +2 more
doaj   +1 more source

Quantum State Discrimination with General Figures of Merit

, 2012
We solve the problem of quantum state discrimination with "general (symmetric) figures of merit" for an even number of symmetric quantum bits with use of the no-signaling principle.
A. S. Holevo, M. A. Nielsen, N. Gisin, R. Tarrach, Won-Young Hwang, Yeong-Deok Han   +5 more
core   +1 more source

Quantifying conditional probabilities of fish-turbine encounters and impacts [PDF]

, 2023
J. Peraza, John K. Horne
openalex   +1 more source

CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions

Advanced Science, EarlyView.
CellPolaris decodes how transcription factors guide cell fate by building gene regulatory networks from transcriptomic data using transfer learning. It generates tissue‐ and cell‐type‐specific networks, identifies master regulators in cell state transitions, and simulates TF perturbations in developmental processes.
Guihai Feng, Xin Qin, Jiahao Zhang, Wuliang Huang, Yiyang Zhang, Wentao Cui, Yao Chen, Shirui Li, Wenhao Liu, Yao Tian, Yana Liu, Jingxi Dong, Ping Xu, Zhenpeng Man, Guole Liu, Zhongming Liang, Xinlong Jiang, Xiaodong Yang, Pengfei Wang, Ge Yang, Hongmei Wang, Xuezhi Wang, Ming‐Han Tong, Yuanchun Zhou, Shihua Zhang, Yiqiang Chen, Yong Wang, Xin Li   +27 more
wiley   +1 more source