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https://www.selleckchem.com/products/pf-562271.html In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infomax rule. Like Infomax, this rule works by controlling the gain and bias of a neuron to regulate its rate of fire. We discuss the biological plausibility of the IP rule and compare it to batch normalisation. We demonstrate that the IP rule improves learning in deep networks, and provides networks with considerable robustness to increases in synaptic learning rates. We also sample the error gradients during learning and show that the IP rule substantially increases the size of the gradients over the course of learning. This suggests that the IP rule solves the vanishing gradient problem. Supplementary analysis is provided to derive the equilibrium solutions that the neuronal gain and bias converge to using our IP rule. An analysis demonstrates that the IP rule results in neuronal information potential similar to that of Infomax, when tested on a fixed input distribution. We also show that batch normalisation also improves information potential, suggesting that this may be a cause for the efficacy of batch normalisation-an open problem at the time of this writing.Hearing aids are the primary tool in non-medical rehabilitation for individuals with hearing loss. While the costs of the electronic components have reduced substantially, the cost of a hearing aid has risen steadily to the point that it has become unaffordable for the majority of the population with Age-Related Hearing Loss (ARHL) especially for those residing in low- and middle-income countries. Here, we present an ultra-low-cost, affordable and accessible hearing aid device ('LoCHAid'), specifically targeted towards treating ARHL in elderly patients. The LoCHAid components cost 98 cents ( less then $1) when purchased in bulk for 10,000 units and can be personalized for each user through a 3D-printable case. It is designed to be an over-the-counter (OTC) self-

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