Results 111 to 120 of about 111,252 (300)
High‐energy electron impact in plasma catalysis often causes excessive dissociation of active intermediates, limiting C2+ product selectivity. To address this challenge, a bio‐inspired stoma‐shell nanoarchitecture is designed to decouple electron impact from catalytic reaction zones.
Nan Zou +5 more
wiley +1 more source
Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP
Spiking neural networks (SNNs) are good candidates to produce ultra-energy-efficient hardware. However, the performance of these models is currently behind traditional methods. Introducing multi-layered SNNs is a promising way to reduce this gap.
Bilasco, Ioan Marius +4 more
core +1 more source
Screening fluorescent voltage probes with spontaneously spiking HEK cells (779.5)
A major difficulty for imaging brain activity comes from the lack of voltage‐sensitive probes that have fast, sensitive and bright characteristics. Unlike other probe development challenges, screening fluorescent voltage probes has been hampered by the low throughput of patch‐clamp characterization. We introduce a line of non‐fluorescent HEK cells that
Jeehae Park +2 more
openaire +1 more source
Development of a transparent, self‐sanitizing antimicrobial coating technology applicable to a wide range of materials and surfaces‐including touchscreens, transparent substrates, and metal, plastic, and glass‐regardless of pathogen type. The spray‐coated, UV‐cross‐linked imidazole‐based quaternary ammonium chloride materials provide broad‐spectrum ...
Surjith Kumaran +6 more
wiley +1 more source
Basic characteristics of epileptiform discharges triggered by lindane in rats [PDF]
Introduction: EEG is a widely used method of epilepsy examination. In order to quantitatively inspect ictal EEG findings, a number of mathematical models have been developed over the years, one of them being the Fast Fourier Transform (FFT).
Useinović Nemanja +8 more
doaj
Pulse Shape and Voltage-Dependent Synchronization in Spiking Neuron Networks
Abstract Pulse-coupled spiking neural networks are a powerful tool to gain mechanistic insights into how neurons self-organize to produce coherent collective behavior. These networks use simple spiking neuron models, such as the θ-neuron or the quadratic integrate-and-fire (QIF) neuron, that replicate the essential features of real ...
openaire +3 more sources
Conductance‐Dependent Photoresponse in a Dynamic SrTiO3 Memristor for Biorealistic Computing
A nanoscale SrTiO3 memristor is shown to exhibit dynamic synaptic behavior through the interaction of local electrical and global optical signals. Its photoresponse depends quantitatively on the conductance state, which evolves and decays over tunable timescales, enabling ultralow‐power, biorealistic learning mechanisms for advanced in‐memory and ...
Christoph Weilenmann +8 more
wiley +1 more source
Summary: Testing whether the synchrony of action potential firing is a cerebellar coding mechanism requires simultaneous recording, with high temporal fidelity, from populations of identified neurons.
Spencer T. Brown +6 more
doaj +1 more source
A compact aVLSI conductance-based silicon neuron
We present an analogue Very Large Scale Integration (aVLSI) implementation that uses first-order lowpass filters to implement a conductance-based silicon neuron for high-speed neuromorphic systems.
Hamilton, Tara Julia +4 more
core +1 more source
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa +19 more
wiley +1 more source

