Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies [PDF]
Bayesian networks (BNs) have been increasingly applied to support management and decision-making processes under conditions of environmental variability and uncertainty, providing logical and holistic reasoning in complex systems since they succinctly ...
Carlo Giupponi, Michela Catenacci
core
We present a complete T2T genome assembly for a key bat reservoir. Integrating population genomics, comparative genomics, transcriptomics, single‐cell omics, and functional assays, we resolve previously inaccessible genomic regions and identify evolutionary signatures associated with immune adaptation.
Yuting Wang +15 more
wiley +1 more source
Subcellular spatial transcriptomics enables high‐resolution mapping of gene expression within tissues, but accurate cell segmentation is essential for assigning transcripts to individual cells. We present SpaCut, a deep learning framework that integrates transcriptomic features with nucleus‐guided morphological information to precisely delineate cell ...
Yongheng Li, Fangfang Zhu, Wenwen Min
wiley +1 more source
Bayesian networks as prognostic models in oncology: a systematic review and recommendations for clinical practice. [PDF]
Reijnen C +7 more
europepmc +1 more source
Neutron depth profiling exploits the 6Li(n,3H)4He reaction to provide quantitative, isotope‐specific, depth‐resolved maps of lithium inside operating lithium‐ion batteries, directly linking lithium transport, dendrite growth and interfacial short‐circuiting to a physics‐informed machine‐learning roadmap that turns this non‐destructive operando ...
Yulong Zhang +8 more
wiley +1 more source
Expression of Concern: Modeling the social drivers of environmental sustainability among Amazonian indigenous lands using Bayesian networks. [PDF]
PLOS One Editors.
europepmc +1 more source
Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons
Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
wiley +1 more source
ReLink: Reliable Deep Learning for Microscopic Motion Tracking
ReLink enables reliable trajectory linking in single‐particle tracking by integrating physics‐informed motion statistics with confidence‐based adaptive filtering. Across diverse simulated and experimental conditions, ReLink robustly reconstructs trajectories and preserves the fidelity of downstream analyses, enabling accurate characterization of ...
Yuan Jiang +7 more
wiley +1 more source
Unraveling Spatiotemporal Heterogeneity and Driving Mechanism of Vegetation Recovery in Co-Seismic Landslide Areas via Nonlinear Trajectories and Bayesian Networks. [PDF]
Wan M, Zhao W, Wu J, Yang Y, Zhao J.
europepmc +1 more source
Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang +9 more
wiley +1 more source

