Results 131 to 140 of about 438,874 (275)

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

open access: yesAdvanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin   +11 more
wiley   +1 more source

Triple‐Mode Ferroelectric Thin‐Film Transistor for Hybrid Electrical–Optical Reservoir Computing

open access: yesAdvanced Science, EarlyView.
A triple‐mode ferroelectric thin‐film transistor is developed by integrating Si3N4/HZO/IGZO layers to realize three independent memory modes: electric long‐term, electric short‐term, and optical short‐term. This single‐device architecture functions as both a reservoir and readout layer, achieving 92.43% MNIST accuracy. It offers a fully hardware‐based,
Hyeonho Lee   +9 more
wiley   +1 more source

Investigating syllabic prominence with conditional random fields and latent-dynamic conditional random fields

open access: yesInterspeech 2012, 2012
CUTUGNO, FRANCESCO   +3 more
openaire   +2 more sources

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

open access: yesAdvanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar   +10 more
wiley   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

open access: yesAdvanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai   +3 more
wiley   +1 more source

Phase‐Resolved Defect Transport Mechanisms Governing Asynchronous Ordering in a Eutectic High‐Entropy Alloy

open access: yesAdvanced Science, EarlyView.
Phase‐resolved experiments and atomistic simulations reveal asynchronous ordering behaviors in a eutectic high‐entropy alloy during isothermal annealing. Distinct defect transport mechanisms are identified in coexisting B2 and BCC phases, showing that vacancy and interstitial mediated diffusion governs phase‐dependent thermal stability.
Huiwen Yao   +5 more
wiley   +1 more source

CONDITIONAL SIMULATION OF SPATIOTEMPORAL RANDOM FIELDS OF ENVIRONMENTAL CONTAMINATION

open access: yesTASK Quarterly, 2006
The paper considers a method of conditional simulation of spatiotemporal scalar random fields of certain environmental phenomena. The method can be used to predict field values at given space points at specified time, on the basis of field values at ...
ROBERT JANKOWSKI, HENRYK WALUKIEWICZ
doaj  

G6PC Downregulation Promotes Renal Calcium Oxalate Stone Formation via Lactate‐Induced SNAIL1 K206 Lactylation and Epithelial‐Mesenchymal Transition

open access: yesAdvanced Science, EarlyView.
In renal calcium oxalate stone formation, G6PC downregulation leads to lactate accumulation. This lactate mediates CBP/p300‐dependent lactylation of SNAIL1 at K206, promoting its nuclear translocation. Nuclear SNAIL1 activates the TGF‐β/SMAD3 pathway, driving epithelial‐mesenchymal transition and fibrosis, which ultimately facilitates crystal ...
Kai Liu   +16 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

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