Results 171 to 180 of about 2,628,917 (279)
A method to generate multivariate data with moments arbitrary close to the desired moments [PDF]
We show how it is possible to generate multivariate data which have moments arbitrary close to the desired ones. They are generated as linear combinations of variables with known theoretical moments.
Lyhagen, Johan
core
HNRNPD promotes radioresistance in nasopharyngeal carcinoma by enhancing stress granule assembly and sequestering GRAMD4 mRNA. This suppresses GRAMD4 translation and inhibits mitochondrial apoptosis. Targeting the integrated stress response with ISRIB restores GRAMD4 expression and sensitizes tumors to radiotherapy, revealing a translational control ...
Yingzi Li +13 more
wiley +1 more source
Classification and Parameter Selection for Damage Characterization in CFRP Composite Materials Using Acoustic Emission and Multivariate Statistics. [PDF]
Amoateng-Mensah D +4 more
europepmc +1 more source
Decoding Rocks: An Assessment of Geomaterial Microstructure Using X-ray Microtomography, Image Analysis and Multivariate Statistics. [PDF]
Strzelecki PJ +5 more
europepmc +1 more source
Tools for Exploring Multivariate Data: The Package ICS
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivariate data. It includes as a special case a method for recovering the unmixing matrix in independent components analysis (ICA).
Klaus Nordhausen +2 more
core
THUMPD1 drives a tumor‐suppressive signaling cascade in lung adenocarcinoma by promoting IGF2R expression. IGF2R associates with PPP2R1A to suppress AKT and activate AMPK, leading to SLC31A1 upregulation and copper accumulation. Elevated copper disrupts mitochondrial metabolism and induces excessive mitophagy, thereby restraining tumor growth and ...
Kai Wu +10 more
wiley +1 more source
Revealing gait as a murine biomarker of injury, disease, and age with multivariate statistics and machine learning. [PDF]
Naved BA +10 more
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
In this article, Shuai and colleagues demonstrate that metabolic remodeling drives self‐diploidization in murine haploid ESCs (haESCs). Mitochondrial dysfunction and imbalanced pyruvate metabolism underlie this process. Genome‐wide screening using haESCs identifies key mitochondrial quality‐control related genes, enabling a metabolism‐based medium that
Yi Fu +11 more
wiley +1 more source

