Results 71 to 80 of about 9,156,471 (236)
Knowledge Graph Driven Grain Big Data Applications: Overview and Perspective
[Significance]Grain production spans multiple stages and involves numerous heterogeneous factors, including agronomic inputs, natural resources, environmental conditions, and socio-economic variables. However, the associated data generated throughout the
YANG Chenxue, LI Xian, ZHOU Qingbo
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Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Traditional temporal knowledge graph completion (TKGC) methods often rely on random encoding or pre‐trained small‐scale language models to initialize entity and relation embeddings. Despite the remarkable reasoning and understanding capabilities of large
Lan Zhao +5 more
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Friend, Not Foe: Lowered Tissue Reactivity to Long‐Term Polyimide Implants
The choice of optimal neural probe designs remains a major challenge in the field of neurotechnology. This study investigated the biocompatibility of several probe variations, including material, thickness, width, and implantation strategy. It highlights the clear advantage of soft polyimide probes over stiff silicon probes for better device ...
Corinne Orlemann +11 more
wiley +1 more source
Subgraph Reasoning on Temporal Knowledge Graphs for Forecasting Based on Relaxed Temporal Relations
Reasoning over Temporal Knowledge Graphs (TKGs) aims to forecast future events based on historical ones. Existing approaches typically enforce strict temporal order constraints among past events; however, such rigidity limits the effective exploitation ...
Meini Yang +3 more
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Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Single‐cell transcriptomics of soybean roots soon after rhizobial inoculation reveals epidermal and cortical cell‐specific programs and gene‐regulatory networks acting in symbiosis establishment. We identify an ethylene‐driven regulatory circuit involving WRKY6.3/6.4 transcription factors targeting select Nod19 genes that promotes infection‐thread ...
Yongbin Zhuang +17 more
wiley +1 more source
Polydopamine nanoparticles enable a precise, non‐genetic, and transcranial neuromodulation strategy via near‐infrared photothermal stimulation. By activating TRPV1 channels, this approach specifically enhances hippocampal gamma oscillations, thereby rescuing spatial memory deficits in models of perioperative neurocognitive disorder.
Yan‐Bo Zhou +10 more
wiley +1 more source
BackgroundThe clinical progression of chronic gastritis involves intricate temporal dependencies, which makes it difficult to capture both the dynamic trajectory of the disease and the underlying relationships among medical events using conventional ...
Xiaolong Qu +8 more
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Mice can transfer the learned rule of spatial working memory to guide similar but novel tasks. Hippocampal CA3 populational activity dynamically reorganize during memory generalization, shifting from task‐specific to generalized coding over testing days. Sparse yet redundant neural representations of CA3 enable rule transfer and cognitive map formation,
Da Song +8 more
wiley +1 more source

