We perform a direct numerical simulation (DNS) of interacting Kelvin–Helmholtz instabilities (KHI) that arise at a stratified shear layer where KH billow cores are misaligned or exhibit varying phases along their axes. Significant evidence of these dynamics in early laboratory shear-flow studies by Thorpe (Geophys. Astrophys. Fluid Dyn., vol. 34, 1985, pp. 175–199) and Thorpe (J. Geophys. Res., vol. 92, 1987, pp. 5231–5248), in observations of KH billow misalignments in tropospheric clouds (Thorpe, Q. J. R. Meteorol. Soc., vol. 128, 2002, pp. 1529–1542) and in recent direct observations of such events in airglow and polar mesospheric cloud imaging in the upper mesosphere reveals that these dynamics are common. More importantly, the laboratory and mesospheric observations suggest that these dynamics lead to more rapid and more intense instabilities and turbulence than secondary convective instabilities in billow cores and secondary KHI in stratified braids between and around adjacent billows. To date, however, no simulations exploring the dynamics and energetics of interacting KH billows (apart from pairing) have been performed. Our DNS performed for Richardson number $Ri=0.10$ and Reynolds number $Re=5000$ demonstrates that KHI tubes and knots (i) comprise strong and complex vortex interactions accompanying misaligned KH billows, (ii) accelerate the transition to turbulence relative to secondary instabilities of individual KH billows, (iii) yield significantly stronger turbulence than secondary KHI in billow braids and secondary convective instabilities in KHI billow cores and (iv) expand the suite of secondary instabilities previously recognized to contribute to KHI dynamics and breakdown to turbulence in realistic geophysical environments.

Fritts et al. (J. Fluid Mech., vol. xx, 2022, xx) describe a direct numerical simulation of interacting Kelvin–Helmholtz instability (KHI) billows arising due to initial billow cores that exhibit variable phases along their axes. Such KHI exhibit strong ‘tube and knot’ dynamics identified in early laboratory studies by Thorpe (Geophys. Astrophys. Fluid Dyn., vol. 34, 1985, pp. 175–199). Thorpe (Q.J.R. Meteorol. Soc., vol. 128, 2002, pp. 1529–1542) noted that these dynamics may be prevalent in the atmosphere, and they were recently identified in atmospheric observations at high altitudes. Tube and knot dynamics were found by Fritts et al. (J. Fluid. Mech., 2022) to drive stronger and faster turbulence transitions than secondary instabilities of individual KH billows. Results presented here reveal that KHI tube and knot dynamics also yield energy dissipation rates $\sim$2–4 times larger as turbulence arises and that remain $\sim$2–3 times larger to later stages of the flow evolution, compared with those of secondary convective instabilities (CI) and secondary KHI accompanying KH billows without tube and knot influences. Elevated energy dissipation rates occur due to turbulence transitions by tube and knot dynamics arising on much larger scales than secondary CI and KHI where initial KH billows are misaligned. Tube and knot dynamics also excite large-scale Kelvin ‘twist waves’ that cause vortex tube and billow core fragmentation, more energetic cascades of similar interactions to smaller scales and account for the strongest energy dissipation events accompanying such KH billow evolutions.

Erikson asked what makes some people care for the future of the species and others not, calling this ‘generativity vs. stagnation’. In three studies, we addressed structure of this trait and its heritability. Study 1 (N = 1570), using structural models of the Loyola Generativity Scale , revealed three correlated factors consisting of (1) Establishing and aiding the next generation; (2) Maintaining the world; and (3) Symbolic immortality through a positive legacy. Study 2 (N = 311) successfully replicated this structure in an independent UK sample. Study 3 tested genetic and environmental influences on generativity. All three factors showed significant and substantial heritable influence. A general factor was required, which was also heritable. In resolving previous uncertainty over the transmission of generativity across generations, shared environmental transmission models fit poorly. Substantial unique environmental effects suggest strong cultural impacts on concern for the species. Generativity researchers may usefully adopt this three-factor scoring system, allowing research on the predictive power of each component of generativity as well as molecular genetic or biological studies.

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

In centrifugal compressors, the identification of flow instability signals from experiments is a difficult problem owing to the nonlinear and non-stationary characteristics. Otherwise, the complicated asymmetric structure of the volute brings a huge challenge to the evolution and circumferential nonuniformity characteristics of the flow instabilities. This paper presents experimental and numerical investigations on internal flow field to understand the flow instability characteristics in a centrifugal compressor. Considering nonlinear and non-stationary signals, a method based on Fourier-transform and variational mode decomposition was introduced to analyse the flow instability characteristics. The Fourier spectrum results show that at 0.21kg/s of 80krpm, the pressure signal has a noticeable high-frequency fluctuation, which indicates that the compressor enters the flow instability state. The variational mode decomposition results show that before a surge, the compressor experiences different flow instability stages: the RI stage, the coexistence stage of RI and stall, and the stall stage. Moreover, obvious circumferential nonuniformity characteristics of flow instabilities were observed during the throttling process. RI first occurred at the 180° circumferential position and then the stall first appeared in the circumferential range of 60° to 240°. The simulation results that it is because that the asymmetric volute causes the adverse pressure gradient inside the impeller passage and a high-pressure region (120°–240°) at the upstream of the impeller inlet. Under this combined action of the two, the effect region of tip leakage vortex expands the upstream of the impeller inlet. Meanwhile, the tip leakage vortex core migrates to a lower span of blades. This study demonstrates the ability to analyse nonlinear and non-stationary signals from a centrifugal compressor via variational mode decomposition, and provides a useful guidance for the identification of flow instability signals.

Digital biomarkers of mental health, created using data extracted from everyday technologies including smartphones, wearable devices, social media and computer interactions, have the opportunity to revolutionise mental health diagnosis and treatment by providing near-continuous unobtrusive and remote measures of behaviours associated with mental health symptoms. Machine learning models process data traces from these technologies to identify digital biomarkers. In this editorial, we caution clinicians against using digital biomarkers in practice until models are assessed for equitable predictions (‘model equity’) across demographically diverse patients at scale, behaviours over time, and data types extracted from different devices and platforms. We posit that it will be difficult for any individual clinic or large-scale study to assess and ensure model equity and alternatively call for the creation of a repository of open de-identified data for digital biomarker development.

Although, biological evidence suggests that tea consumption may protect against non-Hodgkin lymphoma (NHL), epidemiologic evidence has been unclear. The aim of this study was to examine the association between tea-drinking habits and the risk of NHL in a large nationwide prospective cohort of postmenopausal US women. 68,854 women who were enrolled from 1993 through 1998 in the Women’s Health Initiative Observational Study (WHI-OS) and responded to year 3 annual follow-up questionnaire comprised the analytic cohort. Newly diagnosed NHL cases after the year 3 visit were confirmed by medical and pathology reports. Multivariable-adjusted Cox proportional hazards models were performed to assess the associations of tea-drinking habits (specifically, the amounts of caffeinated/herbal/decaffeinated tea intake) with the overall risk of NHL and 3 major subtypes (Diffuse large B-cell lymphoma, DLBCL, (n=195, 0.3%), follicular lymphoma, FL, (n=128, 0.2%), and chronic lymphocytic leukemia/small lymphocytic lymphoma, CLL/SLL, (n=51, 0.1%)). Among 62,622 participants, a total of 663 (1.1%) women developed NHL during a median follow-up of 16.51(SD±6.20) years. Overall, different amounts of type-specific tea intake were not associated with the risk of NHL regardless of its histologic subtypes after adjustment for confounders. Our findings suggest that tea intake at the current consumption level does not influence the risk of NHL, regardless of its histologic types.

Mid- and far-infrared (IR) photometric and spectroscopic observations are fundamental to a full understanding of the dust-obscured Universe and the evolution of both star formation and black hole accretion in galaxies. In this work, using the specifications of the SPace Infrared telescope for Cosmology and Astrophysics (SPICA) as a baseline, we investigate the capability to study the dust-obscured Universe of mid- and far-IR photometry at 34 and $70\, {\rm{\mu }}\mathrm{m}$ and low-resolution spectroscopy at $17{-}36\, {\rm{\mu }}\mathrm{m}$ using the state-of-the-art Spectro-Photometric Realisations of Infrared-selected Targets at all-z (Spritz) simulation. This investigation is also compared to the expected performance of the Origins Space Telescope and the Galaxy Evolution Probe. The photometric view of the Universe of a SPICA-like mission could cover not only bright objects (e.g. $L_{IR}>10^{12}\,{\rm L}_{\odot}$ ) up to ${z}=10$ , but also normal galaxies ( $L_{IR}<10^{11}\,{\rm L}_{\odot}$ ) up to $\textit{z}\sim4$ . At the same time, the spectroscopic observations of such mission could also allow us to estimate the redshifts and study the physical properties for thousands of star-forming galaxies and active galactic nuclei by observing the polycyclic aromatic hydrocarbons and a large set of IR nebular emission lines. In this way, a cold, 2.5-m size space telescope with spectro-photometric capability analogous to SPICA, could provide us with a complete three-dimensional (i.e. images and integrated spectra) view of the dust-obscured Universe and the physics governing galaxy evolution up to $\textit{z}\sim4$ .

The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.

The cosmic evolution of the chemical elements from the Big Bang to the present time is driven by nuclear fusion reactions inside stars and stellar explosions. A cycle of matter recurrently re-processes metal-enriched stellar ejecta into the next generation of stars. The study of cosmic nucleosynthesis and this matter cycle requires the understanding of the physics of nuclear reactions, of the conditions at which the nuclear reactions are activated inside the stars and stellar explosions, of the stellar ejection mechanisms through winds and explosions, and of the transport of the ejecta towards the next cycle, from hot plasma to cold, star-forming gas. Due to the long timescales of stellar evolution, and because of the infrequent occurrence of stellar explosions, observational studies are challenging, as they have biases in time and space as well as different sensitivities related to the various astronomical methods. Here, we describe in detail the astrophysical and nuclear-physical processes involved in creating two radioactive isotopes useful in such studies, $^{26}\mathrm{Al}$ and $^{60}\mathrm{Fe}$ . Due to their radioactive lifetime of the order of a million years, these isotopes are suitable to characterise simultaneously the processes of nuclear fusion reactions and of interstellar transport. We describe and discuss the nuclear reactions involved in the production and destruction of $^{26}\mathrm{Al}$ and $^{60}\mathrm{Fe}$ , the key characteristics of the stellar sites of their nucleosynthesis and their interstellar journey after ejection from the nucleosynthesis sites. This allows us to connect the theoretical astrophysical aspects to the variety of astronomical messengers presented here, from stardust and cosmic-ray composition measurements, through observation of $\gamma$ rays produced by radioactivity, to material deposited in deep-sea ocean crusts and to the inferred composition of the first solids that have formed in the Solar System. We show that considering measurements of the isotopic ratio of $^{26}\mathrm{Al}$ to $^{60}\mathrm{Fe}$ eliminate some of the unknowns when interpreting astronomical results, and discuss the lessons learned from these two isotopes on cosmic chemical evolution. This review paper has emerged from an ISSI-BJ Team project in 2017–2019, bringing together nuclear physicists, astronomers, and astrophysicists in this inter-disciplinary discussion.

Mars exploration motivates the search for extraterrestrial life, the development of space technologies, and the design of human missions and habitations. Here, we seek new insights and pose unresolved questions relating to the natural history of Mars, habitability, robotic and human exploration, planetary protection, and the impacts on human society. Key observations and findings include:

1. – high escape rates of early Mars' atmosphere, including loss of water, impact present-day habitability;

2. – putative fossils on Mars will likely be ambiguous biomarkers for life;

3. – microbial contamination resulting from human habitation is unavoidable; and

4. – based on Mars' current planetary protection category, robotic payload(s) should characterize the local martian environment for any life-forms prior to human habitation.

Some of the outstanding questions are:

1. – which interpretation of the hemispheric dichotomy of the planet is correct;

2. – to what degree did deep-penetrating faults transport subsurface liquids to Mars' surface;

3. – in what abundance are carbonates formed by atmospheric processes;

4. – what properties of martian meteorites could be used to constrain their source locations;

5. – the origin(s) of organic macromolecules;

6. – was/is Mars inhabited;

7. – how can missions designed to uncover microbial activity in the subsurface eliminate potential false positives caused by microbial contaminants from Earth;

8. – how can we ensure that humans and microbes form a stable and benign biosphere; and

9. – should humans relate to putative extraterrestrial life from a biocentric viewpoint (preservation of all biology), or anthropocentric viewpoint of expanding habitation of space?

Studies of Mars' evolution can shed light on the habitability of extrasolar planets. In addition, Mars exploration can drive future policy developments and confirm (or put into question) the feasibility and/or extent of human habitability of space.

Frequent freezing injury greatly influences winter wheat production; thus, effective prevention and a command of agricultural production are vital. The freezing injury monitoring method integrated with ‘3S’ (geographic information systems (GIS), global positioning system (GPS) and remote sensing (RS)) technology has an unparalleled advantage. Using HuanJing (HJ)-1A/1B satellite images of a winter wheat field in Shanxi Province, China plus a field survey, crop types and winter wheat planting area were identified through repeated visual interpretations of image information and spatial analyses conducted in GIS. Six vegetation indices were extracted from processed HJ-1A/1B satellite images to determine whether the winter wheat suffered from freezing injury and its degree of severity and recovery, using change vector analysis (CVA), the freeze injury representative vegetation index and the combination of the two methods, respectively. Accuracy of the freezing damage classification results was verified by determining the impact of freezing damage on yield and quantitative analysis. The CVA and the change of normalized difference vegetation index (ΔNDVI) monitoring results were different so a comprehensive analysis of the combination of CVA and ΔNDVI was performed. The area with serious freezing injury covered 0.9% of the total study area, followed by the area of no freezing injury (3.5%), moderate freezing injury (10.2%) and light freezing injury (85.4%). Of the moderate and serious freezing injury areas, 0.2% did not recover; 1.2% of the no freezing injury and light freezing injury areas showed optimal recovery, 15.6% of the light freezing injury and moderate freezing injury areas showed poor recovery, and the remaining areas exhibited general recovery.