Results 141 to 150 of about 497,808 (317)

Challenges and implications of predicting the spatiotemporal distribution of dengue fever outbreak in Chinese Taiwan using remote sensing data and deep learning

Geo-spatial Information Science
Ongoing climate change has accelerated the outbreak and expansion of climate-sensitive infectious diseases such as dengue fever. Dengue fever will remain a threat until safe and effective vaccines and antiviral drugs have been developed, distributed, and
Sumiko Anno, Hirakawa Tsubasa, Satoru Sugita, Shinya Yasumoto, Ming-An Lee, Yoshinobu Sasaki, Kei Oyoshi   +6 more
doaj   +1 more source

Ultralow‐Dimensionality Reduction for Identifying Critical Transitions by Spatial‐Temporal PCA

Advanced Science, EarlyView.
The proposed spatial‐temporal principal component analysis (stPCA) method analytically reduces high‐dimensional time‐series data to a single latent variable by transforming spatial information into temporal dynamics. By preserving the temporal properties of the original data, stPCA effectively identifies critical transitions and tipping points.
Pei Chen, Yaofang Suo, Kazuyuki Aihara, Ye Li, Dan Wu, Rui Liu, Luonan Chen   +6 more
wiley   +1 more source

MEA‐seqX: High‐Resolution Profiling of Large‐Scale Electrophysiological and Transcriptional Network Dynamics

Advanced Science, EarlyView.
How can we fully understand brain function and disease without uncovering the causal coordination between molecular and neural activity across space and time? MEA‐seqX tackles this challenge by integrating advanced electrophysiology, spatial transcriptomics, and artificial intelligence predictions, revealing multiscale dynamics.
Brett Addison Emery, Xin Hu, Diana Klütsch, Shahrukh Khanzada, Ludvig Larsson, Ionut Dumitru, Jonas Frisén, Joakim Lundeberg, Gerd Kempermann, Hayder Amin   +9 more
wiley   +1 more source

MSLKSTNet: Multi-Scale Large Kernel Spatiotemporal Prediction Neural Network for Air Temperature Prediction

Atmosphere
The spatiotemporal forecasting of temperature is a critical issue in meteorological prediction, with significant implications for fields such as agriculture and energy.
Feng Gao, Jiaen Fei, Yuankang Ye, Chang Liu   +3 more
doaj   +1 more source

Global Stress Generation and Spatiotemporal Super-Resolution Physics-Informed Operator under Dynamic Loading for Two-Phase Random Materials [PDF]

arXiv
Material stress analysis is a critical aspect of material design and performance optimization. Under dynamic loading, the global stress evolution in materials exhibits complex spatiotemporal characteristics, especially in two-phase random materials (TRMs).
arxiv  

3‐HKA Promotes Vascular Remodeling After Stroke by Modulating the Activation of A1/A2 Reactive Astrocytes

Advanced Science, Volume 12, Issue 11, March 20, 2025.
This study identifies 3‐hydroxy‐kynurenamine (3‐HKA) as a significantly downregulated tryptophan metabolite after ischemic stroke. Supplementation with 3‐HKA enhances long‐term neurological recovery by promoting vascular remodeling, through which the regulation of astrocyte A1/A2 transition is mediated by inhibiting AIM2 inflammasome activation.
Jun‐Min Chen, Guang Shi, Lu‐Lu Yu, Wei Shan, Jing‐Yu Sun, An‐Chen Guo, Jian‐Ping Wu, Tie‐Shan Tang, Xiang‐Jian Zhang, Qun Wang   +9 more
wiley   +1 more source

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

, 2021
Robert M. Kanko, Elise K. Laende, Gerda Strutzenberger, Marcus Brown, W. Scott Selbie, Vincent DePaul, Stephen H. Scott, Kevin J. Deluzio   +7 more
openalex   +2 more sources

A Decade of Deep Learning for Remote Sensing Spatiotemporal Fusion: Advances, Challenges, and Opportunities [PDF]

arXiv
Hardware limitations and satellite launch costs make direct acquisition of high temporal-spatial resolution remote sensing imagery challenging. Remote sensing spatiotemporal fusion (STF) technology addresses this problem by merging high temporal but low spatial resolution imagery with high spatial but low temporal resolution imagery to efficiently ...
arxiv  

Machine Learning for Spatiotemporal Sequence Forecasting: A Survey [PDF]

arXiv, 2018
Spatiotemporal systems are common in the real-world. Forecasting the multi-step future of these spatiotemporal systems based on the past observations, or, Spatiotemporal Sequence Forecasting (STSF), is a significant and challenging problem. Although lots of real-world problems can be viewed as STSF and many research works have proposed machine learning
arxiv  

Design Principles From Natural Olfaction for Electronic Noses

Advanced Science, Volume 12, Issue 12, March 27, 2025.
Unlocking “universal smell” requires integrating key principles of natural olfactory systems: modulation of gas transport, utilization of non‐selective sensing elements, chemical filters akin to the biological mucus layer to separate compounds, refined context‐specific signal integration, and more.
Haritosh Patel, Vicente Garrido Portilla, Anna V. Shneidman, Jacopo Movilli, Jack Alvarenga, Christophe Dupré, Michael Aizenberg, Venkatesh N. Murthy, Alexander Tropsha, Joanna Aizenberg   +9 more
wiley   +1 more source