Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural networks for EEG-based brain-computer interfaces remains absent from published work. We address this research gap by using MOABB, The Mother Of All BCI Benchmarks, to compare novel convolutional neural networks to state-of-the-art Riemannian approaches across a broad range of EEG datasets, including motor imagery, P300, and steady-state visual evoked potentials paradigms.We systematically evaluated the performance of convolutional neural networks, specifically EEGNet, shallow ConvNet, and deep ConvNet, against well-established Riemannian decoding methods using MOABB processing pipelines.

Direct Spectroscopic Identification of BN-Arynes and Subtle Steric Effects on Nitrogen Fixation.

1,2-Azaborinines are the BN analogues of arynes through exchange of the formal CC triple bond by an isoelectronic BN bond. The BN-arynes are an underexplored class of reactive intermediates. Dibenzo[c,e][1,2]azaborinine (10,9-BN-phenanthryne) 1 was inferred as reactive intermediate by trapping reactions.

Inhibitors of Fumarylacetoacetate Hydrolase Domain Containing Protein 1 (FAHD1).

(FAHD1) acts as oxaloacetate decarboxylase in mitochondria, contributing to the regulation of the tricarboxylic acid cycle. Guided by a high-resolution X-ray structure of FAHD1 liganded by oxalate, the enzymatic mechanism of substrate processing is analyzed in detail. Taking the chemical features of the FAHD1 substrate oxaloacetate into account, the potential inhibitor structures are deduced.

Disease momentum: Estimating the reproduction number in the presence of superspreading.

A primary quantity of interest in the study of infectious diseases is the average number of new infections that an infected person produces. This so-called reproduction number has significant implications for the disease progression. There has been increasing literature suggesting that superspreading, the significant variability in number of new infections caused by individuals, plays an important role in the spread of SARS-CoV-2.