Results 141 to 150 of about 57,490 (302)

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Retrospective Evaluation of the Topical Use of 1% Amitriptyline in Patients with Burning Mouth Syndrome. [PDF]

Dent J (Basel)
Perez-Parrella CS, Ruiz Roca JA, Pons-Fuster E, López-Jornet P.   +3 more
europepmc   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Manganese Oxidation during Vegetation Burning. [PDF]

Environ Sci Technol
Mariano SMF, Zeng L, Huang R, Sánchez-García C, Santin C, Neris J, Yang P, Ma L, Kiss A.   +8 more
europepmc   +1 more source

Testing liana cutting and controlled burning as silvicultural treatments for a logged forest in the eastern Amazon

, 2001
1. In the eastern Brazilian Amazon, logged forests frequently include patches where liana density is particularly high. In these so-called liana tangles, competition from lianas is predicted to reduce tree growth significantly, thus effectively impeding ...
Gerwing, J
core  

Skin‐Conformal Myography for Real‐Time Hand Tracking Using a Laser‐Induced Graphene Strain Sensor Array

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu, Monther AlSiyabi, Aida Ebrahimi   +2 more
wiley   +1 more source

Topical Piperine for the Management of Burning Mouth Syndrome: A Case Series. [PDF]

J Clin Med
Varoni EM, Meregalli M, Lodi G, Vitalini S, Iriti M, Sardella A.   +5 more
europepmc   +1 more source

Study of burning behavior of small scale wood crib with cone calorimeter

, 2008
Burning behavior of small-scale wood crib was studied by a serial of cone calorimeter tests. The heat release rate curves of these small wood cribs were different due to porosity factor and this shows that the control condition switches from one to ...
Y Jiang (7730723), Christopher Preston (2115640), Qiang Xu (71522), Gregory Griffin (18049642), Glenn Bradbury (19989432), Nathan White (515247), Ashley Bicknell (19995495)   +6 more
core  

Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping

Advanced Intelligent Systems, EarlyView.
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu, Raaid Kabir, Ayodeji Aderibigbe, Oladoyin Kolawole   +5 more
wiley   +1 more source