Results 161 to 170 of about 291 (205)
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source
Electrocatalytic Coupling Conversion of Methane by Dual‐Site Control in Nickel Oxyhydroxide
Electrocatalytic coupling conversion of methane (CH4) is accomplished on the nickel oxyhydroxide (NiOOH), wherein the Ni─O dual‐site is triggered via the proper electronic interaction, synergistically promoting the C─H activation and C─C formation, enabling a selective and efficient C2 product generation route under ambient conditions. ABSTRACT Methane
Kailong Lu +7 more
wiley +1 more source
Periprosthetic joint infection establishes a sophisticated immunosuppressive network between CXCR4+ PMN‐MDSCs and Bregs, inducing profound CD8+ T cell paralysis. Alendronate effectively disrupts this CXCR4+ PMN‐MDSC–Breg axis by targeting STAT3, thereby restoring local immune surveillance.
Jintao Wu +9 more
wiley +1 more source
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source
Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu +4 more
wiley +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
Growth‐Pathway‐Controlled van der Waals Epitaxy of Phase‐Selective Tin Sulfides
Growth‐pathway‐controlled van der Waals epitaxy enables deterministic phase selection and strain engineering in tin sulfide/WSe2 heterostructures. Direct growth of SnS induces substrate‐mediated strain and phase evolution, whereas sequential growth through an SnS2 buffer suppresses strain transfer and stabilizes pristine α‐SnS, revealing a versatile ...
Jaehyeok Lee +2 more
wiley +1 more source
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Nonparametric Probabilistic Optimal Power Flow
IEEE Transactions on Power Systems, 2022With the increasing penetration of renewable energy, accurate and efficient probabilistic optimal power flow (POPF) calculation becomes more and more important to provide decision support for secure and economic operation of power systems. This paper develops a novel nonparametric probabilistic optimal power flow (N-POPF) model describing the ...
Yonghua Song, Can Wan, Yunyi Li
exaly +2 more sources
Toward Fast Calculation of Probabilistic Optimal Power Flow
IEEE Transactions on Power Systems, 2019With the rapid growth of renewables, probabilistic optimal power flow (POPF) has become an important tool to analyze uncertainties in power systems. However, POPF calculation involves repeatedly solving the optimization problem. The computational efficiency has been a major bottleneck for its practical application in power industries.
Wei Dai, , Juan Yu
exaly +2 more sources
The Generalized Cross-Entropy Method in Probabilistic Optimal Power Flow
IEEE Transactions on Power Systems, 2018This paper presents a new powerful density estimator and the application of the generalized cross-entropy method. A framework for probability density function estimation of the probabilistic optimal power flow problem results is presented. Large-scale probabilistic problems have a lot of uncertain parameters, some of which are correlated.
Mohammad Mohammadi +2 more
exaly +2 more sources

