Opposition control of artificially initiated turbulent spots in a laminar boundary layer was carried out in a low-turbulence wind tunnel with the aim to delay transition to turbulence by modifying the turbulent structure within the turbulent spots. The timing and duration of control, which was carried out using wall-normal jets from a spanwise slot, were pre-determined based on the baseline measurements of the transitional boundary layer. The results indicated that the high-speed region of the turbulent spots was cancelled by opposition control, which was replaced by a carpet of low-speed fluid. The application of the variable-interval time-averaging technique on the velocity fluctuation signals demonstrated a reduction in both the burst duration and intensity within the turbulent spots, but the burst frequency was increased.

Background: Despite a higher prevalence of traumatic spinal cord injury (TSCI) amongst Canadian Indigenous peoples, there is a paucity of studies focused on Indigenous TSCI. We present the first Canada-wide study comparing TSCI amongst Canadian Indigenous and non-Indigenous peoples. Methods: This study is a retrospective analysis of prospectively-collected TSCI data from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) from 2004-2019. We divided participants into Indigenous and non-Indigenous cohorts and compared them with respect to demographics, injury mechanism, level, severity, and outcomes. Results: Compared with non-Indigenous patients, Indigenous patients were younger, more female, less likely to have higher education, and less likely to be employed. The mechanism of injury was more likely due to assault or transportation-related trauma in the Indigenous group. The length of stay for Indigenous patients was longer. Indigenous patients were more likely to be discharged to a rural setting, less likely to be discharged home, and more likely to be unemployed following injury. Conclusions: Our results suggest that more resources need to be dedicated for transitioning Indigenous patients sustaining a TSCI to community living and for supporting these patients in their home communities. A focus on resources and infrastructure for Indigenous patients by engagement with Indigenous communities is needed.

The increasing availability of smart products creates a more pronounced need for designers to prototype and communicate interactive and environmental qualities of product during their design process. This paper explores which elements of User journey, Storyboards and Wireframes contribute to communicating these qualities, and how they might integrate with sketching. Results show depictions of user and temporal elements alongside low fidelity sketches are deemed most important. Our findings form the basis to propose and subsequently test combined prototyping approaches in future research.

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.

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.

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.