Results 241 to 250 of about 46,457 (297)

Gait Analysis of Pak Biawak: A Necrobot Lizard Built using the Skeleton of an Asian Water Monitor (Varanus Salvator)

open access: yesAdvanced Robotics Research, EarlyView.
Pak Biawak, a necrobot, embodies an unusual fusion of biology and robotics. Designed to repurpose natural structures after death, it challenges conventional boundaries between nature and engineering. Its movements are precise yet unsettling, raising questions about sustainability, ethics, and the untapped potential of biointegrated machines.
Leo Foulds   +2 more
wiley   +1 more source

NeoNet: A Novel Deep Learning Model for Retinal Disease Diagnosis and Localization. [PDF]

open access: yesSensors (Basel)
Sorgente V   +6 more
europepmc   +1 more source

High‐Performance Graphene‐Based Gas Sensors with Pulsed Heating and AI Processing

open access: yesAdvanced Sensor Research, EarlyView.
Ultra‐low power graphene‐based MEMS gas sensors functionalized with vanadium pentoxide or copper‐manganese oxide are reported. Operated in pulsed heating mode, the sensors produce transient conductance profiles analyzed via discrete Fourier transform and compact neural networks.
Paniz Vafaei   +10 more
wiley   +1 more source

Programmable metal-based immuno-photocatalytic nanoparticles for precision activation of anti-tumor immunity. [PDF]

open access: yesJ Nanobiotechnology
Liu T   +7 more
europepmc   +1 more source

Gas‐ and Liquid‐Phase Catalysts for Solar‐Driven Catalytic Ammonia Decomposition

open access: yesAdvanced Sustainable Systems, EarlyView.
Amid the drive toward carbon‐neutral hydrogen, this review analyzes photocatalytic ammonia decomposition in gas‐ and liquid‐phase systems. It examines catalyst families—TiO2, ZnO, Ru, single‐atom, and antenna–reactor designs. This study summarizes advances in bandgap tuning, active‐site and cocatalyst engineering, photothermal coupling, and machine ...
Zhuohao Yang   +4 more
wiley   +1 more source

Predicting Immunotherapy Outcomes in NSCLC Using RNA and Pathology from Multicenter Clinical Trials

open access: yesAdvanced Science, EarlyView.
LIRA, a machine learning‐based model, is developed using transcriptomic data from 891 NSCLC patients in the OAK and POPLAR cohorts. Its predictive performance is validated in multiple external cohorts. Patients stratified by LIRA‐score exhibit distinct clinical characteristics and tumor microenvironment profiles.
Zhaojun Wang   +32 more
wiley   +1 more source

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