Results 161 to 170 of about 3,951 (305)
We present a tissue‐stimulator platform for seamless electrode integration with pancreatic tissue, applying uniform electrical stimulation through optimized design with biohybrid 3D printing. Advantageous effects of electrical stimulation on β‐cell function were observed, including enhanced calcium signaling, islet morphology, and maturation.
Jihwan Kim +7 more
wiley +1 more source
Flexible piezoresistive pressure sensors underpin wearable and soft electronics. This review links sensing physics, including contact resistance modulation, quantum tunneling and percolation, to unified materials/structure design. We highlight composite and graded architectures, interfacial/porous engineering, and microstructured 3D conductive networks
Feng Luo +2 more
wiley +1 more source
Segmental recurrent neural networks
© ICLR 2016: San Juan, Puerto Rico. All Rights Reserved. We introduce segmental recurrent neural networks (SRNNs) which define, given an input sequence, a joint probability distribution over segmentations of the input and labelings of the segments ...
Kong, Lingpeng +2 more
core
Cyclic Olefin Copolymers as Versatile Materials for Advanced Engineering Applications
Cyclic olefin copolymers (COCs) are presented as highly versatile materials combining tunable synthesis, excellent optical properties, and mechanical robustness. Their potential spans microfluidics, bioengineering, and advanced electronics, while emerging self‐healing and sustainable solutions highlight future opportunities.
Giulia Fredi +3 more
wiley +1 more source
Self‐Healing and Stretchable Synaptic Transistor
A self‐healing stretchable synaptic transistor (3S‐T) is realized using a p‐PVDF‐HFP‐DBP/PDMS‐MPU‐IU bilayer as gate insulator, where dipole‐dipole interaction enhances polarization to achieve a large memory window. Leveraging its neuronal biomimicry, the synaptic transistor demonstrates electrically compatibility with the biological brain. Furthermore,
Hyongsuk Choo +10 more
wiley +1 more source
Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units
There has been a lot of interest in the use of discrete-time recurrent neural nets (DTRNN) to learn nite-state tasks, with interesting results regarding the induction of simple nite-state machines from input–output strings.
Rafael C. Carrasco +3 more
core
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min +13 more
wiley +1 more source
Spatial Transcriptomics Reveals Location-Specific Tumor Cell Subtypes and Signaling within Multifocal Small Intestinal Neuroendocrine Tumors. [PDF]
Yogo A +5 more
europepmc +1 more source
Training recurrent neural networks by the recursive least squares algorithm
In this work a novel approach to the training of recurrent neural nets is presented. The algorithm exploits the separability of each neuron into its linear and nonlinear part. Each iteration of the learning consists of two steps: First the descent of the
RAPAGNETTA A. +3 more
core
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 +19 more
wiley +1 more source

