Results 211 to 220 of about 140,466 (301)

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

HNF-DDA: subgraph contrastive-driven transformer-style heterogeneous network embedding for drug-disease association prediction. [PDF]

BMC Biol
Shang Y, Wang Z, Chen Y, Yang X, Ren Z, Zeng X, Xu L.   +6 more
europepmc   +1 more source

Temporal network embedding framework with causal anonymous walks representations. [PDF]

PeerJ Comput Sci, 2022
Makarov I, Savchenko A, Korovko A, Sherstyuk L, Severin N, Kiselev D, Mikheev A, Babaev D.   +7 more
europepmc   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease. [PDF]

J Transl Med
Su YY, Huang HC, Lin YT, Chuang YF, Sheu SY, Lin CC.   +5 more
europepmc   +1 more source

Novel drug-target interactions via link prediction and network embedding. [PDF]

BMC Bioinformatics, 2022
Amiri Souri E, Laddach R, Karagiannis SN, Papageorgiou LG, Tsoka S.   +4 more
europepmc   +1 more source

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source

Survival prediction and molecular subtyping of squamous cell lung cancer based on network embedding. [PDF]

Sci Rep
Guo D, Chen J, Wang Y, Liu X.
europepmc   +1 more source

Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes

, 2023
Ma J, Li B, Li Q, Fan C, Mostafavi A.
europepmc   +1 more source

Dipole‐Engineered Conductive Additives for Ultrastable Interphase Evolution in High‐Areal‐Capacity Silicon Anodes

Advanced Functional Materials, EarlyView.
In the work reported herein, dipole‐engineered sulfonated carbon nanofibers enable conductive additives to actively regulate interphase formation in silicon anodes. Polar sulfonyl groups guide electrolyte decomposition to form a compact LiF‐rich interphase while promoting robust integration with silicon.
Song Kyu Kang, Hyeonju Kim, Jeongbin Cho, Minseon Park, Taehun Kim, Seonghun Sin, Won Bae Kim   +6 more
wiley   +1 more source