Science

Monkeypox is a viral zoonotic disease endemic in Central and West Africa. In May 2022, dozens of non-endemic countries reported hundreds of monkeypox cases, most with no epidemiological link to Africa. We identified two lineages of monkeypox virus (MPXV) among two 2021 and seven 2022 US monkeypox cases: the major 2022 outbreak variant called B.1 and a minor contemporaneously sampled variant called A.2. Analyses of mutations among these two variants revealed an extreme preference for GA-to-AA mutations indicative of human APOBEC3 cytosine deaminase activity among Clade IIb MPXV (previously West African, Nigeria) sampled since 2017. Such mutations were not enriched within other MPXV clades. These findings suggest that APOBEC3 editing may be a recurrent and a dominant driver of MPXV evolution within the current outbreak.CC999999/ImCDC/Intramural CDC HHSUnited States

Deep Reinforcement Learning for Artificial Upwelling Energy Management

The potential of artificial upwelling (AU) as a means of lifting nutrient-rich bottom water to the surface, stimulating seaweed growth, and consequently enhancing ocean carbon sequestration, has been gaining increasing attention in recent years. This has led to the development of the first solar-powered and air-lifted AU system (AUS) in China. However, efficient scheduling of air injection systems remains a crucial challenge in operating AUS, as it holds the potential to significantly improve system efficiency. Conventional approaches based on rules or models are often impractical due to the complex and heterogeneous nature of the marine environment and its associated disturbances. To address this challenge, we propose a novel energy management approach that utilizes deep reinforcement learning (DRL) algorithm to develop efficient strategies for operating AUS. Through extensive simulations, we evaluate the performance of our algorithm and demonstrate its superior effectiveness over traditional rule-based approaches and other DRL algorithms in reducing energy wastage while ensuring the stable and efficient operation of AUS. Our findings suggest that a DRL-based approach offers a promising way for improving the efficiency of AUS and enhancing the sustainability of seaweed cultivation and carbon sequestration in the ocean.Comment: 31 pages, 13 figure

Assessing fire frequency and structural fire behaviour of England statistics according to BS PD 7974-7

Contemporary structural fire statistics are fundamental in engineering design practice to evaluate likelihood and consequence of fire for different property types, and to investigate how different safety measures impact fire spread. British Standard PD 7974-7:2003 has recently been updated using USA fire statistics; this paper compares PD 7974-7:2003 to current England statistics (named UK statistics) using one public and one Home Office dataset. PD 7974-7:2003 overestimates fire frequency with values up to 5 times greater than the ones found in UK and USA. When fire frequency is plotted against total floor space, for different property types, power laws with positive or negative exponent and polynomial functions provide better approximations of the data than the current codes. Average area damage from PD 7974-7:2003 has been compared to fire and total damage from UK datasets where fire size is usually well confined to room of origin at 20% of fires based on the publicly available dataset. When fires exceeding specific areas of damage are considered, PD 7974-7:2003 usually overestimates fire damage and underestimates total damage, with more damage evident when sprinklers are absent compared to when they are present