Lectures related to Chloride channel

Explores the structure and function of nicotinic receptors, focusing on Cys-loop receptors, ion conductance, and the effects of nicotine.

Explores the granulation of ceramic suspension through atomization and related processes such as slip casting and density measurements.

Explores the structure and function of ion channels, including their rapid conformational changes and key features like open probability.

Explores the cellular mechanisms and speed of action potential propagation in neurons.

Demonstrates dry grinding using a rotary ball mill and emphasizes safety measures.

Explores hydraulic constructions, wave propagation, and bedload analysis for project design.

Explores the generation and propagation of action potentials in neurons, including the historical significance of Hodgkin & Huxley's work.

Covers an introduction to Pega platform 8.5.3 and its key features.

Covers the concept of stationarity in continuous-time stochastic processes and its applications in communication systems.

Covers the wrapping and decoding process of polar codes, exploring the trade-off between quality and efficiency in lossy compression.

Explores weight sharing, filters, channels, and data augmentation in convolutional neural networks.

Discusses quantifying protein X localization relative to Golgi and Mitochondria in 2D confocal images.

Explores cellular mechanisms of brain function, focusing on ion channels and action potentials.

Explores the physical basis of signal propagation in neurons, focusing on membrane potential setup and ion channels.

Explores error correction codes, decoding algorithms, and their role in communication systems.

Covers the role of ion channels in biological processes, from bacterial resistance to neuronal signaling and pain modulation.

Explores the voltage-gating kinetics of Na+ and K+ channels, including rapid opening and inactivation of Na+ channels.

Showcases 3D confocal stacks with cell markers and nanoparticles, exploring nanoparticle penetration and location assessment.

Explores convolutional neural networks, covering convolution, cross-correlation, max pooling, layer structure, and examples like LeNet5 and AlexNet.

Covers the motivation and architecture of convolutional networks, from LeNet to AlexNet.