Results 81 to 90 of about 35,745,185 (300)

Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package

Journal of Statistical Software, 2019
This paper describes the R package mvLSW. The package contains a suite of tools for the analysis of multivariate locally stationary wavelet (LSW) time series.
Simon A. C. Taylor, Timothy Park, Idris A. Eckley   +2 more
doaj   +1 more source

Fuzzy clustering of univariate and multivariate time series by genetic multiobjective optimization [PDF]

Given a set of time series, it is of interest to discover subsets that share similar properties. For instance, this may be useful for identifying and estimating a single model that may fit conveniently several time series, instead of performing the usual
S. Bandyopadhyay, R. Baragona, U. Maulik
core  

Stress Hyperglycemia Drives CD4+ T Cell PANoptosis and Postoperative Organ Injury via Monocyte‐Derived Succinate

Advanced Science, EarlyView.
High glucose is linked to reduced succinate dehydrogenase activity in CD14+ monocytes, accompanied by succinate accumulation and extracellular release. Extracellular succinate exacerbates mitochondrial ROS production and mtDNA release in CD4+ T cells. Cytosolic mtDNA then activates Z‐DNA binding protein 1 (ZBP1) and engages ZBP1‐associated inflammatory
Shuai Zhao, Xuemei Miao, Wei Luo, Tao Liu, Yang Wang, Jiaying Li, Di Fu, Weiyun Shen, Yan Luo, Kang Chen, Ruping Dai, Hui Li   +11 more
wiley   +1 more source

Distributional reservoir state analysis for real-time anomaly detection in multivariate time series data

npj Artificial Intelligence
Real-time anomaly detection in time series data is crucial for domains including system monitoring, health care, and manufacturing. Here, real-time capability encompasses both minimal detection delays and quick training, enabling timely intervention and ...
Hiroto Tamura, Kantaro Fujiwara, Kazuyuki Aihara, Gouhei Tanaka   +3 more
doaj   +1 more source

Bootstrapping frequency domain tests in multivariate time series with an application to comparing spectral densities [PDF]

We propose a general bootstrap procedure to approximate the null distribution of nonparametric frequency domain tests about the spectral density matrix of a multivariate time series.
Paparoditis, Efstathios, Dette, Holger
core  

Journal of Multivariate Experimental Personality and Clinical Psychology, v.1, no.4 (complete version)

, 1975
The fourth issue of the Journal of Multivariate Experimental Personality and Clinical Psychology edited by G.R. Pierson. Editorial policy board: R.B. Cattell, H.J. Eysenck, J.P. Guilford and P.E.

core   +1 more source

circZNF148 Drives Glucose Metabolism Reprogramming to Enhance Metastasis and Immune Evasion via HK1 Stabilization in Triple‐Negative Breast Cancer

Advanced Science, EarlyView.
CircZNF148 stabilizes HK1 through deubiquitinase recruitment, thereby enhancing glycolysis and lactate production. Elevated lactate promotes PD‑L1 lactylation and membrane accumulation while suppressing CD8+ T‐cell cytotoxicity, collectively facilitating immune evasion and malignant progression in TNBC.
Yuhan Jin, Wenjing Zhao, Lei Wang, Jianing Wang, Keying Zhao, Dan Luo, Yifei Wang, Yuxia Yang, Jingze Yang, Yaming Li, Tong Chen, Dianwen Han, Zekun Wang, Xiaoyan Li, Bing Chen, Lijuan Wang, Yiran Liang, Qifeng Yang   +17 more
wiley   +1 more source

Emotional states predict cellular immune system activity under conditions of life as it is lived: A multivariate time-series analysis approach. [PDF]

PLoS One, 2023
Seizer L, Fuchs D, Bliem HR, Schubert C.
europepmc   +1 more source

The vector innovation structural time series framework: a simple approach to multivariate forecasting [PDF]

The vector innovation structural time series framework is proposed as a way of modelling a set of related time series. Like all multi-series approaches, the aim is to exploit potential inter-series dependencies to improve the fit and forecasts.
Rob J. Hyndman, Ashton de Silva, Ralph D. Snyder   +2 more
core  

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source