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The COVID-19 pandemic is spreading rapidly around the world, causing countries to impose lockdowns and efforts to develop vaccines on a global scale. However, human-to-animal and animal-to-human transmission cannot be ignored, as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can spread rapidly in farmed and wild animals. This could create a worrying cycle of SARS-CoV-2 spillover from humans to animals and spillback of new strains back into humans, rendering vaccines ineffective. This study provides a key indicator of animals that may be potential susceptible hosts for SARS-CoV-2 and coronavirus infections by analysing the phylogenetic distance between host angiotensin-converting enzyme 2 and the coronavirus spike protein. Crucially, our analysis identifies animals that are at elevated risk from a spillover and spillback incident. One group of animals has been identified as potentially susceptible to SARS-CoV-2 by harbouring a parasitic coronavirus spike protein similar to the SARS-CoV-2 spike protein. These animals may serve as amplification hosts in spillover events from zoonotic reservoirs. Tracing interspecies transmission in multi-host environments based solely on in vitro and in vivo examinations of animal susceptibility or serology is a time-consuming task. This approach allows rapid identification of high-risk animals to prioritize research and assessment of the risk of zoonotic disease transmission in the environment. It is a tool to rapidly identify zoonotic species that may cause outbreaks or participate in expansion cycles of coexistence with their hosts. This prevents the spread of coronavirus infections between species, preventing spillover and spillback incidents from occurring.

Programmable biomolecule-mediated computing is a new computing paradigm as compared to contemporary electronic computing. It employs nucleic acids and analogous biomolecular structures as information-storing and -processing substrates to tackle computational problems. It is of great significance to investigate the various issues of programmable biomolecule-mediated processors that are capable of automatically processing, storing, and displaying information. This Perspective provides several conceptual designs of programmable biomolecule-mediated processors and provides some insights into potential future research directions for programmable biomolecule-mediated processors.

A multiphase flowmeter (MPFM) is used in the upstream oil and gas industry for continuous, in-line, real-time, oil-gas-water flow measurement without fluid separation. An MPFM typically consists of phase-fraction (holdup) and velocity (or flow rate) measurements. It is desirable to have homogeneous flow at the measurement location so that the phase-fraction measurement is representative. A horizontal blind-tee pipe-section is often installed to homogenize flow in the downstream vertical Venturi-based flowmeters; however, little information is available on the effect of horizontal blind-tee depth (HBD) on flow homogeneity. In addition, the Venturi vertical entrance length (VEL) leading to the Venturi inlet from the horizontal blind-tee outlet is another design parameter that may potentially affect the downstream phase distribution. The phase-fraction measurement principle requires liquid properties (e.g. water salinity). The local liquid richness makes the horizontal blind-tee an ideal location for measuring liquid properties; however, an excessive HBD may affect the reliability of the measurements of liquid properties, because local vortices may degrade liquid measurement representativeness if the local liquid velocity is too low. This study uses a computational fluid dynamics approach to evaluate the effect of HBD and VEL on multiphase flow measurement, including the Venturi differential-pressure, the Venturi inlet and the throat phase-fraction, and the local liquid-property at the end of a horizontal blind-tee. The computational results are validated with experimental data collected in a multiphase flow facility. Appropriate HBD and VEL are recommended.

Real-time in-line interpretation of liquid properties is important for multiphase flow measurements. Therefore, it would be desirable to have a sensor, such as a microwave sensor, which can continuously measure the salinity of a flow. In addition to salinity measurement, the microwave sensor can also measure water fraction, which is required for a multiphase flowmeter based on single-energy gamma-ray attenuation; however, choosing a suitable probe sensing location for a microwave salinity sensor in a multiphase flowmeter can be challenging, as the sensor needs to be located at near-wall liquid-rich region to accommodate a wide range of flow conditions. Currently, a microwave sensor is installed in the lower area of a horizontal blind-tee inlet spool of a multiphase flowmeter for salinity measurement. Integrating the microwave sensor into the vertically mounted multiphase flowmeter can reduce the flowmeter (carbon) footprint and manufacturing costs and can improve water-to-liquid ratio measurement due to faster local oil-water mixing. The associated challenge is that the sensor needs to be located at near-wall liquid-rich region to accommodate a wide range of flow conditions, including high gas-volume-fraction flows, where the near-wall liquid layer present in the vertical pipe is usually very thin. In this study, computational fluid dynamics modeling is used to evaluate the suitability of four different sensing locations along the vertical cross-section of a Venturi-based multiphase flowmeter based on near-wall liquid-richness. The results show that the Venturi inlet is the most suitable location for microwave sensor measurement, compared to the mid-convergence section, the mid-divergence section, and the Venturi outlet for a range of inlet liquid-volume-fractions. The findings have been validated by experimental microwave sensor measurements in a multiphase flow loop facility.

Although lessons have been learned from previous severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, the rapid evolution of the viruses means that future outbreaks of a much larger scale are possible, as shown by the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, it is necessary to better understand the evolution of coronaviruses as well as viruses in general. This study reports a comparative analysis of the amino acid usage within several key viral families and genera that are prone to triggering outbreaks, including coronavirus (SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-HKU1, HCoV-OC43, HCoV-NL63, HCoV-229E), influenza A (H1N1, H3N2), flavivirus (dengue virus serotypes 1-4, Zika) and ebolavirus (Zaire, Sudan, Bundibugyo ebolavirus). Our analysis reveals that the distribution of amino acid usage in the viral genome is constrained to follow a linear order, and the distribution remains closely related to the viral species within the family or genus. This constraint can be adapted to predict viral mutations and future variants of concern. By studying previous SARS and MERS outbreaks, we have adapted this naturally occurring pattern to determine that although pangolin plays a role in the outbreak of COVID-19, it may not be the sole agent as an intermediate animal. In addition to this study, our findings contribute to the understanding of viral mutations for subsequent development of vaccines and toward developing a model to determine the source of the outbreak.

The incomplete version of the Macdonald function has various appellations in literature and earns a well-deserved reputation of being a computational challenge. This paper ties together the previously disjoint literature and presents the basic properties of the incomplete Macdonald function, such as recurrence and differential relations, series and asymptotic expansions. This paper also shows that the incomplete Macdonald function, as a simple closed-form expression, is a particular solution to a parabolic partial differential equation, which arises naturally in a wide variety of transient and diffusion-related phenomena.