Results 51 to 60 of about 8,962 (250)
Stationarity Exploration for Multivariate Time Series Forecasting
Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular for accurately exploring periodic patterns. However, existing methods often cannot effectively explore stationary information from complex intertwined frequency components.
Hao Liu +4 more
openaire +2 more sources
Turning Water Into a Tool: From Degradation Pathways to Functional Engineering in Halide Perovskites
Water exhibits a threshold‐dependent dual role in lead halide perovskites, acting either as a degradation trigger or as a powerful tool for defect passivation, recrystallization, and structural engineering. This review discusses how controlled water‐mediated interactions govern stability, dimensionality, and optoelectronic performance, providing ...
Raphaella T. S. Gonçalves +4 more
wiley +1 more source
Deep Coupling Network for Multivariate Time Series Forecasting
Multivariate time series (MTS) forecasting is crucial in many real-world applications. To achieve accurate MTS forecasting, it is essential to simultaneously consider both intra- and inter-series relationships among time series data. However, previous work has typically modeled intra- and inter-series relationships separately and has disregarded multi ...
Kun Yi 0001 +6 more
openaire +2 more sources
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
BackTime: Backdoor Attacks on Multivariate Time Series Forecasting
23 pages.
Xiao Lin 0016 +4 more
openaire +3 more sources
Dissecting the Ecological Structure of Health and Disease in the Global Gut Microbiome
We introduce Wiredancer, a framework that identifies three continuous ecological factors of the gut microbiota. These factors exhibit distinct patterns across health and disease, jointly capturing disrupted ecological stability and offering a new perspective for precision diagnostics and therapeutic strategies.
Baoyuan Zhu +19 more
wiley +1 more source
This study identifies palmitoylation as a novel regulatory modification of SMAD4, mediated by ZDHHC22/APT2. It activates fatty acid synthesis, creating a self‐reinforcing SMAD4–FASN–palmitate feedback loop that drives pancreatic cancer growth and enhances radiotherapy sensitivity.
Yang Wang +16 more
wiley +1 more source
Icariin promoted the growth of Akk by enhancing the activity of N‐acetylgalactosaminidase (Amuc_0920), which enhanced mucin utilization and provided a favorable nutrient environment for bacterial growth. This icariin‐mediated enrichment of Akk further reshaped the tumor microenvironment and promoted CD8+ T cell infiltration, ultimately synergizing with
Shuangying Qiao +12 more
wiley +1 more source
Channel-Wise Retrieval for Multivariate Time Series Forecasting
Multivariate time series forecasting often struggles to capture long-range dependencies due to fixed lookback windows. Retrieval-augmented forecasting addresses this by retrieving historical segments from memory, but existing approaches rely on a channel-agnostic strategy that applies the same references to all variables.
Junhyeok Kang +6 more
openaire +2 more sources
A single‐cell atlas of pancreatic ductal adenocarcinoma development reveals progressive ductal‐fibroblast‐immune crosstalk. Tumor‐derived LAMB3 drives the formation of immunosuppressive LRRC15+ fibroblasts through the ITGB1/FAK/MAPK/FOSL2 signaling. Glycolytic reprogramming upregulates LAMB3 and correlates with LRRC15+ fibroblast enrichment.
Xuqing Shi +23 more
wiley +1 more source

