Results 221 to 230 of about 424,186 (295)

Smart REASSURED Sensors via Machine‐Augmented Printable On‐Paper Arrays

open access: yesAdvanced Sensor Research, EarlyView.
This perspective highlights the emerging role of pattern‐recognition, printable on‐paper sensor arrays for intelligent PoC diagnostics. It discusses how paper's inherent limitations can be overcome through surface modification and scalable printing, and how machine‐learning analysis of cross‐reactive arrays enables multiplexed, low‐cost, and REASSURED ...
Naimeh Naseri, Saba Ranjbar
wiley   +1 more source

Blood Pressure in Adolescence and Atherosclerosis in Middle Age.

open access: yesJAMA Cardiol
Herraiz-Adillo Á   +11 more
europepmc   +1 more source

Photoelectrochemical Hydrogen Production Using TiO2/Mn‐CdS Photoanode with ZnS Passivation and CoPi as Hole Transfer Relay

open access: yesAdvanced Sustainable Systems, EarlyView.
The electrode features TiO2 as a stable UV‐absorbing substrate, Mn‐doped CdS to extend light absorption into the visible range, ZnS to prevent CdS photocorrosion, and an outer cobalt phosphate (CoPi) that catalyzes oxygen evolution, efficiently enhancing hole transfer from the photoanode to the electrolyte.
Hwapyong Kim   +4 more
wiley   +1 more source

Hg-Lampe [PDF]

open access: yes, 2019
openaire   +1 more source

Capillary Dynamics Analysis of Millimetric Tubes for Anti‐Slip Surfaces: A Phase‐Field Based Finite Element Approach and Experimental Validation

open access: yesAdvanced Theory and Simulations, EarlyView.
Phase‐field method based numerical modelling of the capillary rise in millimeter‐sized tubes, aiming for anti‐slip applications. The experimental validation was performed through capillary assays in polyethylene oxide (PEO) bulk modified polydimethylsiloxane (PDMS) channels.
Shivam Sharma   +7 more
wiley   +1 more source

First‐Principles Structure–Activity Relationship Insights Into Phenolic Scaffolds: QSAR Modeling and Drug‐Likeness Screening

open access: yesAdvanced Theory and Simulations, EarlyView.
Integrated machine learning framework for phenolic derivatives: classification (toxicity) and regression (logP) models identify top drug‐like compounds. Random Forest outperformed for toxicity, while Linear Regression best predicted logP. A weighted scoring approach prioritized five safe, lipophilicity‐optimized candidates, supporting rational ...
Houria Nacer   +7 more
wiley   +1 more source

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