The recent expansion of cross-cultural research in the social sciences has led to increased discourse on methodological issues involved when studying culturally diverse populations. However, discussions have largely overlooked the challenges of construct validity – ensuring instruments are measuring what they are intended to – in diverse cultural contexts, particularly in developmental research. We contend that cross-cultural developmental research poses distinct problems for ensuring high construct validity owing to the nuances of working with children, and that the standard approach of transporting protocols designed and validated in one population to another risks low construct validity. Drawing upon our own and others’ work, we highlight several challenges to construct validity in the field of cross-cultural developmental research, including (1) lack of cultural and contextual knowledge, (2) dissociating developmental and cultural theory and methods, (3) lack of causal frameworks, (4) superficial and short-term partnerships and collaborations, and (5) culturally inappropriate tools and tests. We provide guidelines for addressing these challenges, including (1) using ethnographic and observational approaches, (2) developing evidence-based causal frameworks, (3) conducting community-engaged and collaborative research, and (4) the application of culture-specific refinements and training. We discuss the need to balance methodological consistency with culture-specific refinements to improve construct validity in cross-cultural developmental research.

The variable stator vanes (VSV) are a set of typical spatial linkage mechanisms widely used in the variable cycle engine compressor. Various factors influence the angle adjustment precision of the VSV, leading to the failure of the mechanism. The reliability analysis of VSV is a complex task due to the involvement of multiple components, high dimensionality input and computational inefficiency. Considering the hierarchical characteristics of VSV structure, we propose a novel multi-layer Kriging surrogate (MLKG) for the reliability analysis of VSV. The MLKG combines multiple Kriging surrogate models arranged in a hierarchical structure. By breaking the problem down into more minor problems, MLKG works by presenting each small problem as a Kriging model and reducing the input dimension of the sub-layer Kriging model. In this way, the MLKG can capture the complex interactions between the inputs and outputs of the problem while maintaining a high degree of accuracy and efficiency. This study proves the error propagation process of MLKG. To evaluate MLKG’s accuracy, we test it on two typical high-dimensional non-linearity functions (Rosenbrock and Michalewicz function). We compared MLKG with some contemporary KG surrogate modeling techniques using mean squared error (MSE) and R square (${R^2}$). Results show that MLKG achieves an excellent level of accuracy for reliability analysis in high-dimensional problems with a small number of sample points.

In order to investigate the three-dimensional effects on the flow characteristics of the thin water film for the three-dimensional wings, the numerical simulation of the droplet impingement and film flow on the MS-0317 wing is implemented based on the open-source package OpenFOAM. The simulation focuses on the effects of the angle-of-attack and the angle of sweepback. The movement and impingement of the droplets are calculated using the Lagrangian method, and the film flow is simulated using the thin film assumption and the finite area method. The simulation of the water film flow of the three-dimensional MS-0317 wing shows that there is a spanwise flow of the water film due to the three-dimensional effects. This suggests that more research should be conducted on the warm glaze ice with surface water film of three-dimensional ice accretion on three-dimensional geometries.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

We report the experimental results of the commissioning phase in the 10 PW laser beamline of the Shanghai Superintense Ultrafast Laser Facility (SULF). The peak power reaches 2.4 PW on target without the last amplifying during the experiment. The laser energy of 72 ± 9 J is directed to a focal spot of approximately 6 μm diameter (full width at half maximum) in 30 fs pulse duration, yielding a focused peak intensity around 2.0 × 1021 W/cm2. The first laser-proton acceleration experiment is performed using plain copper and plastic targets. High-energy proton beams with maximum cut-off energy up to 62.5 MeV are achieved using copper foils at the optimum target thickness of 4 μm via target normal sheath acceleration. For plastic targets of tens of nanometers thick, the proton cut-off energy is approximately 20 MeV, showing ring-like or filamented density distributions. These experimental results reflect the capabilities of the SULF-10 PW beamline, for example, both ultrahigh intensity and relatively good beam contrast. Further optimization for these key parameters is underway, where peak laser intensities of 1022–1023 W/cm2 are anticipated to support various experiments on extreme field physics.

The International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) found that there was no statistical difference in cardiovascular events with an initial invasive strategy as compared with an initial conservative strategy of guideline-directed medical therapy for patients with moderate to severe ischemia on noninvasive testing. In this study, we describe the reasons that potentially eligible patients who were screened for participation in the ISCHEMIA trial did not advance to enrollment, the step prior to randomization. Of those who preliminarily met clinical inclusion criteria on screening logs submitted during the enrollment period, over half did not participate due to physician or patient refusal, a potentially modifiable barrier. This analysis highlights the importance of physician equipoise when advising patients about participation in randomized controlled trials.

There are numerous examples of translational science innovations addressing challenges in the translational process, accelerating progress along the translational spectrum, and generating solutions relevant to a wide range of human health needs. Examining these successes through an education lens can identify core principles and effective practices that lead to successful translational outcomes. The National Center for Advancing Translational Sciences (NCATS) is identifying and teaching these core principles and practices to a broad audience via online courses in translational science which teach from case studies of NCATS-led or supported research initiatives. In this paper, we share our approach to the design of these courses and offer a detailed description of our initial course, which focused on a preclinical drug discovery and development project spanning academic and government settings. Course participants were from a variety of career stages and institutions. Participants rated the course high in overall value to them and in providing a unique window into the translational science process. We share our model for course development as well as initial findings from the course evaluation with the goal of continuing to stimulate development of novel education activities teaching foundational principles in translational science to a broad audience.

We report on experimental observation of non-laminar proton acceleration modulated by a strong magnetic field in laser irradiating micrometer aluminum targets. The results illustrate the coexistence of ring-like and filamentation structures. We implement the knife edge method into the radiochromic film detector to map the accelerated beams, measuring a source size of 30–110 μm for protons of more than 5 MeV. The diagnosis reveals that the ring-like profile originates from low-energy protons far off the axis whereas the filamentation is from the near-axis high-energy protons, exhibiting non-laminar features. Particle-in-cell simulations reproduced the experimental results, showing that the short-term magnetic turbulence via Weibel instability and the long-term quasi-static annular magnetic field by the streaming electric current account for the measured beam profile. Our work provides direct mapping of laser-driven proton sources in the space-energy domain and reveals the non-laminar beam evolution at featured time scales.

There is a paucity of evidence about the prevalence and risk factors for symptomatic infection among children. This study aimed to describe the prevalence of symptomatic coronavirus disease 2019 (COVID-19) and its risk factors in children and adolescents aged 0–18 years in Qatar. We conducted a cross-sectional study of all children aged 0–18 years diagnosed with COVID-19 using polymerase chain reaction in Qatar during the period 1st March to 31st July 2020. A generalised linear model with a binomial family and identity link was used to assess the association between selected factors and the prevalence of symptomatic infection. A total of 11 445 children with a median age of 8 years (interquartile range (IQR) 3–13 years) were included in this study. The prevalence of symptomatic COVID-19 was 36.6% (95% confidence interval (CI) 35.7–37.5), and it was similar between children aged <5 years (37.8%), 5–9 years (34.3%) and 10 + years (37.3%). The most frequently reported symptoms among the symptomatic group were fever (73.5%), cough (34.8%), headache (23.2%) and sore throat (23.2%). Fever (82.8%) was more common in symptomatic children aged <5 years, while cough (38.7%) was more prevalent in those aged 10 years or older, compared to other age groups. Variables associated with an increased risk of symptomatic infection were; contact with confirmed cases (RD 0.21; 95% CI 0.20–0.23; P = 0.001), having visited a health care facility (RD 0.54; 95% CI 0.45–0.62; P = 0.001), and children aged under 5 years (RD 0.05; 95% CI 0.02–0.07; P = 0.001) or aged 10 years or older (RD 0.04; 95% CI 0.02–0.06; P = 0.001). A third of the children with COVID-19 were symptomatic with a higher proportion of fever in very young children and a higher proportion of cough in those between 10 and 18 years of age.

We developed a passive sampler for time-integrated collection and radiocarbon (14C) analysis of soil respiration, a major flux in the global C cycle. It consists of a permanent access well that controls the CO2 uptake rate and an exchangeable molecular sieve CO2 trap. We tested how access well dimensions and environmental conditions affect collected CO2, and optimized cleaning procedures to minimize 14CO2 memory. We also deployed two generations of the sampler in Arctic tundra for up to two years, collecting CO2 over periods of 3 days–2 months, while monitoring soil temperature, volumetric water content, and CO2 concentration. The sampler collects CO2 at a rate proportional to the length of a silicone tubing inlet (7–26 µg CO2-C day-1·m Si-1). With constant sampler dimensions in the field, CO2 recovery is best explained by soil temperature. We retrieved 0.1–5.3 mg C from the 1st and 0.6–13 mg C from the 2nd generation samplers, equivalent to uptake rates of 2–215 (n=17) and 10–247 µg CO2-C day-1 (n=20), respectively. The method blank is 8 ± 6 µg C (mean ± sd, n=8), with a radiocarbon content (fraction modern) ranging from 0.5875–0.6013 (n=2). The sampler enables more continuous investigations of soil C emission sources and is suitable for Arctic environments.

Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.