Results 101 to 110 of about 31,731,507 (308)
Symbolic Methods for Exploring Infinite State Spaces.
In this thesis, we introduce a general method for computing the set of reachable states of an infinite-state system. The basic idea, inspired by well-known state-space exploration methods for finite-state systems, is to propagate reachability from the initial state of the system in order to determine exactly which are the reachable states.
openaire +3 more sources
State space analysis of diphtheria pathogenesis using semi-tensor products and permutation methods [PDF]
In this study, we analyze the state space of a Boolean network modeling diphtheria pathogenesis, focusing on key genes such as Tox, Rep, INF1/INF2, TLR, AP1, IL6, and TNF.
Ugbene Ifeanyichukwu Jeff +1 more
doaj
Linear Offset-Free Model Predictive Control in the Dynamic PLS Framework
This work addresses the model predictive control (MPC) of the offset-free tracking problem in the dynamic partial least square (DyPLS) framework. Firstly, state space MPC based on the DyPLS is proposed.
Ligang Hou, Ze Wu, Xin Jin, Yue Wang
doaj +1 more source
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Output controllability of impulsive Boolean control networks based on hybrid‐index model
In biological systems, impulses are often used to model mutations in gene expression. In order to describe the instantaneity of the impulse, this paper employs a hybrid‐index model of impulsive Boolean networks with state‐triggered impulses.
Qianya Liang +3 more
doaj +1 more source
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
Cointegration Analysis with State Space Models [PDF]
This paper presents and exemplifies results developed for cointegration analysis with state space models by Bauer and Wagner in a series of papers. Unit root processes, cointegration and polynomial cointegration are defined.
Wagner, Martin
core
Drug resistance limits treatment success in a subset of lung cancers driven by ROS1 gene alterations. Using patient‐derived cells and computer simulations, we studied three key mutations and how they affect five targeted drugs. The mutations reduced drug effectiveness in different ways by altering protein structure and behavior.
Farhan Ul Haq +8 more
wiley +1 more source
Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models [PDF]
The impact of parameterisation on the simulation efficiency of Bayesian Markov chain Monte Carlo (MCMC) algorithms for two non-Gaussian state space models is examined.
Chris M Strickland +2 more
core
Circulating microRNAs as biomarkers of cachexia and sex‐specific cancer in senior dogs. In 25 client‐owned dogs, four circulating miRNAs (miR‐15a, miR‐15b, miR‐16, miR‐140) were downregulated in cachexia, with miR‐16 the strongest individual biomarker (AUC = 0.899).
Soon‐Seok Park +6 more
wiley +1 more source

