An anti-spiking charity says it has not seen a fall in reports although official figures are down.

A British man has been found guilty of sexual assault and other crimes for tricking a pregnant woman into drinking a liquid that contained abortion drugs to induce a miscarriage, unbeknownst to the victim.

Climate change is extending mosquito season and helping to drive outbreaks of dengue fever, Oropouche virus and eastern equine encephalitis

Spiking neural networks (SNNs) are considered as a potential candidate to overcome current challenges such as the high-power consumption encountered by artificial neural networks (ANNs), however there is still a gap between them with respect to the recognition accuracy on practical tasks. A conversion strategy was thus introduced recently to bridge this gap by mapping a trained ANN to an SNN. However, it is still unclear that to what extent this obtained SNN can benefit both the accuracy advantage from ANN and high efficiency from the spike-based paradigm of computation. In this paper, we propose two new conversion methods, namely TerMapping and AugMapping. The TerMapping is a straightforward extension of a typical threshold-balancing method with a double-threshold scheme, while the AugMapping additionally incorporates a new scheme of augmented spike that employs a spike coefficient to carry the number of typical all-or-nothing spikes occurring at a time step. We examine the performance of our methods based on MNIST, Fashion-MNIST and CIFAR10 datasets. The results show that the proposed double-threshold scheme can effectively improve accuracies of the converted SNNs. More importantly, the proposed AugMapping is more advantageous for constructing accurate, fast and efficient deep SNNs as compared to other state-of-the-art approaches. Our study therefore provides new approaches for further integration of advanced techniques in ANNs to improve the performance of SNNs, which could be of great merit to applied developments with spike-based neuromorphic computing.

Jeremy R. Manning
Oct 28, 2009; 29:13613-13620
BehavioralSystemsCognitive

Everybody promised to destroy HFC-23 but apparently they didn't.

As the coronavirus pandemic sweeps the world, more and more governments are imposing lockdowns on their citizens. As a result, reliance on digital tools has increased significantly to maintain social and professional relationships. Notably, usage of video conferencing app Zoom has spiked, and not just for professional purposes.

But what about the social media tools we were already using to connect with people on a daily basis? How has their popularity changed so far in these trying times?

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Held for spiking fuel