The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an important, and potentially advantageous, source of control signals. To demonstrate how control signals can be derived from such plan activity we performed a computational study with neural activity previously recorded from the posterior parietal cortex of rhesus monkeys planning arm movements. We employed maximum likelihood decoders to estimate movement direction and to drive finite state machines governing when to move. Performance exceeded 90% with as few as 40 neurons.

In order to investigate the clinical features of pregnant women and their neonates with coronavirus disease 2019 (COVID-19) and the evidence of vertical transmission of COVID-19, we retrieved studies included in PubMed, Medline and Chinese databases from January 1, 2000 to October 25, 2020 using relevant terms, such as 'COVID-19', 'vertical transmission' et al. in 'Title/Abstract'. Case reports and case series were included according to the inclusion and exclusion criteria. We conducted literature screening and data extraction, and performed literature bias risk assessment. Total of 13 case series and 16 case reports were collected, including a total of 564 pregnant women with COVID-19 and their 555 neonates, of which 549 neonates received nucleic acid test for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 18 neonates was diagnosed with COVID-19. The positive rate is 3.28%. Amniotic fluid of one woman was tested positive for SARS-CoV-2. The majority of infected neonates were born under strict infection control and received isolation and artificial feeding. Up till now, there is no sufficient evidence to exclude the possibility of vertical transmission for COVID-19 based on the current available data.

Under an industry-related high-temperature oxidation atmosphere, the structure and chemical states of metal nanocatalysts meeting sustainable development challenges change dramatically, deteriorating the activity and/or lowering the yield. Theoretically revealing the mechanisms of oxygen-induced structure evolution and establishing a framework to distinguish them are vital to improving the operando stability and rational design of metal nanocatalysts. Here, we studied the oxygen-induced disintegration and Ostwald ripening of Ni, Cu, Pt, Pd, and Ag nanoparticles on TiO2(110) using first-principles-based thermodynamic and kinetic simulations. It was found that oxygen promotes Ostwald ripening via the formation of Ag/Ag–O and Pd intermediates on the support and volatile gaseous PtO2 complexes, induces disintegration of Ni nanoparticles to Ni–O complexes, and leads to the formation of copper oxide. These differences in the deactivation pathways can be attributed to the dependence of the ripening activation energies and disintegration free energies on the interaction between metal atoms/complexes and TiO2(110). Revealed knowledge and corresponding models provide valuable insights into the general mechanisms governing the structural evolution of supported nanocatalysts under reaction conditions.

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