Background: Modelling COVID-19 transmission at live events and public gatherings is essential to controlling the probability of subsequent outbreaks and communicating to participants their personalized risk. Yet, despite the fast-growing body of literature on COVID-19 transmission dynamics, current risk models either neglect contextual information including vaccination rates or disease prevalence or do not attempt to quantitatively model transmission. Objective: This paper attempted to bridge this gap by providing informative risk metrics for live public events, along with a measure of their uncertainty. Methods: Building upon existing models, our approach ties together 3 main components: (1) reliable modelling of the number of infectious cases at the time of the event, (2) evaluation of the efficiency of pre-event screening, and (3) modelling of the event's transmission dynamics and their uncertainty using Monte Carlo simulations. Results: We illustrated the application of our pipeline for a concert at the Royal Albert Hall and highlighted the risk's dependency on factors such as prevalence, mask wearing, and event duration. We demonstrate how this event held on 3 different dates (August 20, 2020; January 20, 2021; and March 20, 2021) would likely lead to transmission events that are similar to community transmission rates (0.06 vs 0.07, 2.38 vs 2.39, and 0.67 vs 0.60, respectively). However, differences between event and background transmissions substantially widened in the upper tails of the distribution of the number of infections (as denoted by their respective 99th quantiles: 1 vs 1, 19 vs 8, and 6 vs 3, respectively, for our 3 dates), further demonstrating that sole reliance on vaccination and antigen testing to gain entry would likely significantly underestimate the tail risk of the event. Conclusions: Despite the unknowns surrounding COVID-19 transmission, our estimation pipeline opens the discussion on contextualized risk assessment by combining the best tools at hand to assess the order of magnitude of the risk. Our model can be applied to any future event and is presented in a user-friendly RShiny interface. Finally, we discussed our model's limitations as well as avenues for model evaluation and improvement.

Cobalamin (vitamin B-12) is a cofactor for essential metabolic reactions in multiple eukaryotic taxa, including major primary producers such as algae, and yet only prokaryotes can produce it. Many bacteria can colonize the algal phycosphere, forming stable communities that gain preferential access to photosynthate and in return provide compounds such as B-12. Extended coexistence can then drive gene loss, leading to greater algal-bacterial interdependence. In this study, we investigate how a recently evolved B-12-dependent strain of Chlamydomonas reinhardtii, metE7, forms a mutualism with certain bacteria, including the rhizobium Mesorhizobium loti and even a strain of the gut bacterium E. coli engineered to produce cobalamin. Although metE7 was supported by B-12 producers, its growth in co-culture was slower than the B-12-independent wild-type, suggesting that high bacterial B-12 provision may be necessary to favour B-12 auxotrophs and their evolution. Moreover, we found that an E. coli strain that releases more B-12 makes a better mutualistic partner, and although this trait may be more costly in isolation, greater B-12 release provided an advantage in co-cultures. We hypothesize that, given the right conditions, bacteria that release more B-12 may be selected for, particularly if they form close interactions with B-12-dependent algae.

Using argon as the pressure medium, the structural and elastic properties of NiO have been investigated up to 67 GPa by the in situ synchrotron x-ray diffraction in a diamond anvil cell. Up to 67 GPa, NiO remains in the rhombohedral distorted rocksalt structure without phase transition. The lattice parameters of a and c, indexed in the hexagonal lattice, were found to decrease monotonically with increasing pressure, while the c/a ratio remains almost constant. The elastic properties of NiO were studied by analyzing the linewidth of various diffraction perks, which indicates that the factor S = (S-11-S-12-S-44/2) is negative although the single-crystal elastic compliances S11 is positive, respectively, in the investigated pressure range. (c) 2008 American Institute of Physics. [DOI: 10.1063/1.3031697]

High-pressure strength and plastic properties of nanocrystalline tantalum carbide (nano-TaC) have been investigated by using synchrotron radiation up to 65.5 GPa. Nano-TaC shows a bulk modulus of K-0 = 433 +/- 7 GPa with K-0' fixed at 4.0. It is close to that of diamond and is higher than the results from micron-TaC. In its plastic deformation behavior, nano-TaC starts to yield a plastic deformation at around 20 GPa, and the yield strength of nano-TaC increases with pressures and reaches a value of similar to 22 GPa at the highest pressure in our test. The high-pressure strength of nano-TaC is comparable to that of other superhard metals such as B6O, c-BC2N and gamma-Si3N4. The first-principle DFT calculations confirm a lower bulk modulus for micron-TaC. (C) 2013 Elsevier Ltd. All rights reserved.

High-energy synchrotron x-ray diffraction was utilized to study the local order of liquid sulfur at high-pressure and high-temperature conditions. A temperature driven structure change in liquid sulfur was observed, signified by an order of magnitude reduction in lengths of sulfur chains. The large change in chain length implies that this is a liquid-liquid phase transition in sulfur. The chain breakage may strongly influence the physical properties, such as the semiconductor-metal transition and a drastic decrease in viscosity across the transition.

Understanding the volume collapse phenomena in rare-earth materials remains an important challenge due to a lack of information on 4f electronic structures at different pressures. Here, we report the first high-pressure inelastic X-ray scattering measurement on elemental cerium (Ce) metal. By overcoming the ultralow signal issue in the X-ray measurement at the Ce N-4,N-5-edge, we observe the changes of unoccupied 4f states across the volume collapse transition around 0.8 GPa. To help resolve the longstanding debate on the Anderson-Kondo and Mott-Hubbard models, we further compare the experiments with extended multiplet calculations that treat both screening channels on equal footing. The results indicate that a modest change in the 4f-5d Kondo coupling can well describe the spectral redistribution across the volume collapse, whereas the hybridization between neighboring atoms in the Hubbard model appears to play a minor role. Our study helps to constrain the theoretical models and opens a promising new route for systematic investigation of volume collapse phenomena in rare-earth materials.

Successful development of wind farms relies on the optimal siting of wind turbines to maximize the power capacity under stochastic wind conditions and wake losses caused by neighboring turbines. This paper presents a novel method to quickly generate approximate optimal layouts to support infrastruc-ture design decisions. We model the quadratic integer formulation of the discretized layout design problem with an undirected graph that succinctly captures the spatial dependencies of the design pa-rameters caused by wake interactions. On the undirected graph, we apply probabilistic inference using sequential tree-reweighted message passing to approximate turbine siting. We assess the effectiveness of our method by benchmarking against a state-of-the-art branch and cut algorithm under varying wind regime complexities and wind farm discretization resolutions. For low resolutions, probabilistic infer-ence can produce optimal or nearly optimal turbine layouts that are within 3% of the power capacity of the optimal layouts achieved by state-of-the-art formulations, at a fraction of the computational cost. As the discretization resolution (and thus the problem size) increases, probabilistic inference produces optimal layouts with up to 9% more power capacity than the best state-of-the-art solutions at a much lower computational cost.