Results 61 to 70 of about 7,721,766 (241)

Robust covariance estimation for data fusion from multiple sensors [PDF]

, 2011
This paper addresses the robust estimation of a covariance matrix to express uncertainty when fusing information from multiple sensors. This is a problem of interest in multiple domains and applications, namely, in robotics.
Lazarus, Samuel B., Samuel B. Lazarus, Tsourdos, Antonios, Antonios Tsourdos, João Sequeira, Sequeira, João   +5 more
core   +1 more source

Selenium Nanoparticles Selectively Target KRAS G13D to Inhibit Colorectal Cancer

Advanced Science, EarlyView.
The mechanisms of SeNPs therapy in cancer treatment, encompass three parallel actions: (1) seleno‐amino acids, key metabolites, upregulate GPX2 expression, thereby inhibiting tumor metastasis via the GPX2‐HIF1α‐VEGF signaling pathway; (2) selenite (SeO32−), an inorganic metabolite, forms hydrogen bonds with amino acid residues 13–17 of the KRAS G13D ...
Xiaoting Liu, Chong Wu, Shiyao Song, Li Ma, Shaoqing Huang, Yuting He, Qinghai Li, Yanzhou Chang, Dan Jiang, Yong Mei, Junchao Cai, Zhenshuang Du, Tianfeng Chen, Weiling He   +13 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Structural covariance in subcortical stroke patients measured by automated MRI-based volumetry

NeuroImage: Clinical, 2019
A network-level investigation of the volumetric changes of subcortical stroke patients is still lacking. Here, we explored the alterations of structural covariance caused by subcortical stroke with automated brain volumetry.
Caihong Wang, Lei Zhao, Yishan Luo, Jingchun Liu, Peifang Miao, Sen Wei, Lin Shi, Jingliang Cheng   +7 more
doaj   +1 more source

Network Level Structural Covariance in Individuals at Ultra-High Risk (UHR) for Psychosis

, 2023
Network Level Structural Covariance in Individuals at Ultra-High Risk (UHR) for ...
Renate Reniers (13452873), Kareen Heinze (13744306), Ben Harrison (3330927), Ashleigh Lin (2622058), Barnaby Nelson (13390896), S J Wood (13452600), Alison Yung (13100928)   +6 more
core  

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

Advanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

Topological regularization of networks in temporal lobe epilepsy: a structural MRI study

Frontiers in Neuroscience
ObjectivePatients with temporal lobe epilepsy (TLE) often exhibit neurocognitive disorders; however, we still know very little about the pathogenesis of cognitive impairment in patients with TLE.
Yini Chen, Lu Sun, Shiyao Wang, Beiyan Guan, Jingyu Pan, Yiwei Qi, Yufei Li, Nan Yang, Hongsen Lin, Ying Wang, Bo Sun   +10 more
doaj   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Advanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais, S. Peng, J. Chang, F. Li, Q. Zhu, K. Yuan, G. Hugelius, H. Li, Y. Cai, F. Chevallier, K. Tibrewal, E. A. Kort, K. Arndt, J. Watts, B. Buma, N. Besic, P. I. Palmer, H. Cadillo‐Quiroz, E. Euskirchen, M. J. Gondwe, A. Hoyt, R. Jackson, S. Malone, D. Monteverde, S. Natali, M. Ramonet, C. Rey‐Sanchez, L. B. Sagang, E. A. G. Schuur, R. Vargas, R. Varner, Z. Zhang, B. Poulter   +32 more
wiley   +1 more source

Using individualized structural covariance networks to analyze the heterogeneity of cerebral small vessel disease with depressive states

Frontiers in Neurology
ObjectivesCerebral small vessel disease (CSVD) is a heterogeneous cerebrovascular syndrome with a variety of pathological mechanisms and clinical manifestations.
Shiyu Zhang, Yue Chen, Hua Zhou, Zhong Zhao   +3 more
doaj   +1 more source