Predicting the dispersal of SARS-CoV-2 RNA from the wastewater treatment plant to the coast.

Viral pathogens including SARS-CoV-2 RNA have been detected in wastewater treatment effluent, and untreated sewage overflows, that pose an exposure hazard to humans. We assessed whether SARS-CoV-2 RNA was likely to have been present in detectable quantities in UK rivers and estuaries during the first wave of the Covid-19 pandemic. We simulated realistic viral concentrations parameterised on the Camel and Conwy catchments (UK) and their populations, showing detectable SARS-CoV-2 RNA concentrations for untreated but not for treated loading, but also being contingent on viral decay, hydrology, catchment type/shape, and location. Under mean or low river flow conditions, viral RNA concentrated within the estuaries allowing for viral build-up and caused a lag by up to several weeks between the peak in community infections and the viral peak in the environment. There was an increased hazard posed by SARS-CoV-2 RNA with a T 90 decay rate >24 h, as the estuarine build-up effect increased. High discharge events transported the viral RNA downstream and offshore, increasing the exposure risk to coastal bathing waters and shellfisheries - although dilution in this case reduced viral concentrations well below detectable levels. Our results highlight the sensitivity of exposure to viral pathogens downstream of wastewater treatment, across a range of viral loadings and catchment characteristics - with implications to environmental surveillance.

Priorities to inform research on marine plastic pollution in Southeast Asia.

Southeast Asia is considered to have some of the highest levels of marine plastic pollution in the world. It is therefore vitally important to increase our understanding of the impacts and risks of plastic pollution to marine ecosystems and the essential services they provide to support the development of mitigation measures in the region. An interdisciplinary, international network of experts (Australia, Indonesia, Ireland, Malaysia, the Philippines, Singapore, Thailand, the United Kingdom, and Vietnam) set a research agenda for marine plastic pollution in the region, synthesizing current knowledge and highlighting areas for further research in Southeast Asia. Using an inductive method, 21 research questions emerged under five non-predefined key themes, grouping them according to which: (1) characterise marine plastic pollution in Southeast Asia; (2) explore its movement and fate across the region; (3) describe the biological and chemical modifications marine plastic pollution undergoes; (4) detail its environmental, social, and economic impacts; and, finally, (5) target regional policies and possible solutions. Questions relating to these research priority areas highlight the importance of better understanding the fate of marine plastic pollution, its degradation, and the impacts and risks it can generate across communities and different ecosystem services. Knowledge of these aspects will help support actions which currently suffer from transboundary problems, lack of responsibility, and inaction to tackle the issue from its point source in the region. Being profoundly affected by marine plastic pollution, Southeast Asian countries provide an opportunity to test the effectiveness of innovative and socially inclusive changes in marine plastic governance, as well as both high and low-tech solutions, which can offer insights and actionable models to the rest of the world.

Does adiabatic quantum optimization fail for NP-complete problems?

It has been recently argued that adiabatic quantum optimization would fail in solving NP-complete problems because of the occurrence of exponentially small gaps due to crossing of local minima of the final Hamiltonian with its global minimum near the end of the adiabatic evolution. Using perturbation expansion, we analytically show that for the NP-hard problem known as maximum independent set, there always exist adiabatic paths along which no such crossings occur. Therefore, in order to prove that adiabatic quantum optimization fails for any NP-complete problem, one must prove that it is impossible to find any such path in polynomial time.

Finding low-energy conformations of lattice protein models by quantum annealing.

Lattice protein folding models are a cornerstone of computational biophysics. Although these models are a coarse grained representation, they provide useful insight into the energy landscape of natural proteins. Finding low-energy threedimensional structures is an intractable problem even in the simplest model, the Hydrophobic-Polar (HP) model. Description of protein-like properties are more accurately described by generalized models, such as the one proposed by Miyazawa and Jernigan (MJ), which explicitly take into account the unique interactions among all 20 amino acids. There is theoretical and experimental evidence of the advantage of solving classical optimization problems using quantum annealing over its classical analogue (simulated annealing). In this report, we present a benchmark implementation of quantum annealing for lattice protein folding problems (six different experiments up to 81 superconducting quantum bits). This first implementation of a biophysical problem paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.

Federated repositories of X-ray diffraction images.

There is a pressing need for the archiving and curation of raw X-ray diffraction data. This information is critical for validation, methods development and improvement of archived structures. However, the relatively large size of these data sets has presented challenges for storage in a single worldwide repository such as the Protein Data Bank archive. This problem can be avoided by using a federated approach, where each institution utilizes its institutional repository for storage, with a discovery service overlaid. Institutional repositories are relatively stable and adequately funded, ensuring persistence. Here, a simple repository solution is described, utilizing Fedora open-source database software and data-annotation and deposition tools that can be deployed at any site cheaply and easily. Data sets and associated metadata from federated repositories are given a unique and persistent handle, providing a simple mechanism for search and retrieval via web interfaces. In addition to ensuring that valuable data is not lost, the provision of raw data has several uses for the crystallographic community. Most importantly, structure determination can only be truly repeated or verified when the raw data are available. Moreover, the availability of raw data is extremely useful for the development of improved methods of image analysis and data processing.