Results 111 to 120 of about 18,244,857 (290)
Advanced Science, EarlyView.An electronics‐free smart scleral lens passively monitors dry eye disease‐related tear biomarkers through colorimetric sensing of chloride, pH, and ocular surface temperature. Smartphone‐assisted image analysis enables quantitative interpretation, providing a simple, non‐invasive strategy for ocular health monitoring without integrated electronics ...
Ziheng Wang +15 more
wiley +1 more source
Diagonal Adaptive Graph: Revisiting Channel Dependency in Multivariate Time Series Forecasting
InformationAdaptive graph learning has become a widely adopted paradigm for multivariate time series forecasting when explicit physical topology is unavailable. In these approaches, node embeddings are typically used to construct dense adjacency matrices based on ...
Xiang Li, Yanping Zheng, Zhewei Wei
doaj +1 more source
Temporal aggregation of univariate and multivariate time series models: A survey [PDF]
We present a unified and up-to-date overview of temporal aggregation techniques for univariate and multivariate time series models explaining in detail how these techniques are employed.
Andrea Silvestrini, David Veredas
core
Advanced Science, EarlyView.DIXDC1 drives bladder cancer progression by binding and stabilizing DLAT. This axis enhances NEK7 and CCNE2 mRNA stability to promote proliferation and lymphatic metastasis, while limiting copper‐induced DLAT oligomerization to reduce cuproptosis sensitivity, identifying DIXDC1 as a potential target linking metastasis with cuproptosis resistance ...
Hongqiong Li +17 more
wiley +1 more source
Forecasting Time Series from Clusters. [PDF]
Forecasting large numbers of time series is a costly and time-consuming exercise. Before forecasting a large number of series that are logically connected in some way, the authors can first cluster them into groups of similar series.
Inder, B., Marahaj, E.A.
core
The Interplay of Curvature, Geometry, and Topology Shapes Tissue Organisation in Epithelial Shells
Advanced Science, EarlyView.Purely geometric 3D Voronoi models predict the organisation of epithelial shells. The interplay of curvature, geometry, and topology enriches the number of pentagons in shells with lower number of cells. Small MDCK cysts and Mouse embryos match the top polygonal configurations in a compactness‐based ranking derived from the Voronoi model. In conclusion,
Laura Morato +9 more
wiley +1 more source
工程科学学报Multivariate time-series forecasting is a core technology for a wide range of critical applications, including intelligent scheduling, risk management, and resource allocation in complex modern systems. Although transformer-based models have demonstrated
Nianwen NING +6 more
doaj +1 more source
Conformal Multistep-Ahead Multivariate Time-Series Forecasting.
, 2022 This paper proposes a method for conformal multistep-ahead multivariate time-series forecasting. The method minimizes the coverage loss when the data exchangeability assumption does not properly hold. This is done by weighting residual quantiles while computing prediction intervals. Preliminary experiments on real data demonstrate the method’s utility.
Filip Schlembach +2 more
openaire +2 more sources
Advanced Science, EarlyView.Oligosaccharides with defined glycosidic bonds drive divergent gut microbial succession and shape unique metabolic profiles. Absolute time‐series profiling with Bayesian generalized Lotka–Volterra modeling identifies bond‐specific microbial responders, while monoculture validation and metaproteomics reveal linkage‐matched transport and cleavage modules.
Xiaoxuan Lu +10 more
wiley +1 more source
Trend-Error Decomposition for Self-Supervised Time Series Learning in Multivariate Forecasting Task
IEEE AccessSelf-Supervised Learning (SSL) has become a powerful paradigm in Artificial Intelligence, enabling the training of machine learning models using unlabeled data.
Sara Pederzoli +3 more
doaj +1 more source