Richtmyer–Meshkov instability (RMI) at quasi-single-mode interfaces subjected to strong shocks with Mach number exceeding 3.0 is investigated through shock-tube experiments. To reveal the influence of higher-order initial modes, one single-mode and four quasi-single-mode interfaces with varying modal compositions are examined. The Richtmyer theory is experimentally verified for the first time to accurately capture the single-mode interface evolution from start-up to the linear stage. In contrast, it fails for quasi-single-mode scenarios, highlighting the significant effect of higher-order modes. By incorporating the influence of higher-order modes via linear superposition, a linear model for quasi-single-mode interface evolution is proposed, whose validation indicates negligible modal coupling in early evolution. For the nonlinear period, a representative model for weak-shock-driven RMI at a single-mode interface performs poorly, as it does not consider the influence of higher-order modes and key mechanisms such as shock proximity, secondary compression and spike acceleration. Based on the present findings, an empirical nonlinear model with favourable predictive capability is developed. Furthermore, by matching the new linear and nonlinear models, a complete description of the amplitude evolution of single-mode and quasi-single-mode interfaces from start-up to nonlinear stages is achieved, offering new insight into modelling strong-shock-driven RMI.

Spatial linear instability analysis is employed to investigate the instability of a viscoelastic liquid jet in a co-flowing gas stream. The theoretical model incorporates a non-uniform axial base profile represented by a hyperbolic tangent, capturing the shear layer. The Oldroyd-B model discretised with Chebyshev polynomials is employed, and energy budget analysis is used to interpret underlying mechanisms. At low Weber numbers, the jet evolves axisymmetrically and the instability is governed by interfacial gas-pressure fluctuations; as the Weber number increases, the growing inertia drives a transition of the predominant mode from axisymmetric to helical. At weak elasticity, the instability is also primarily governed by gas-pressure fluctuations. As elasticity increases, the predominant mode transitions from axisymmetric to helical. This transition is accompanied by a migration of disturbance structures from the interface toward the jet interior and an enhanced coupling between velocity perturbation and the basic flow. These trends reveal a new predominant instability mechanism – the elasticity-enhanced shear-driven instability – which is distinct from capillary or Kelvin–Helmholtz instabilities in Newtonian jets. A $\textit{We}$–$El$ phase diagram delineates the boundary between predominant modes and experimental results obtained in a flow-focusing configuration validate the theoretical predictions. Compared with temporal stability results, the spatial framework – by directly resolving the convective downstream amplification of disturbances – achieves quantitative agreement with experiments and highlights the superiority of spatial instability analysis in capturing the dynamics of strongly convective, non-parallel jet flows. These findings provide mechanistic insight into viscoelastic jet instabilities and offer guidance for applications involving droplet and fibre formation in co-flow systems.

What determines countries’ successful transition to democracy? This article explores the impact of granting civil rights in authoritarian regimes and especially the gendered aspect of this process. It argues that both men's and women's liberal rights are essential conditions for democratisation to take place: providing both women and men rights reduces an inequality that affects half of the population, thus increasing the costs of repression and enabling the formation of women's organising – historically important to spark protests in initial phases of democratisation. This argument is tested empirically using data that cover 173 countries over the years 1900–2012 and contain more nuanced measures than commonly used. Through novel sequence analysis methods, the results suggest that in order to gain electoral democracy a country first needs to furnish civil liberties to both women and men.

This study examines the reform and development of trade associations in Shanghai, China, one of the main economic hubs of the country and marked by a substantial growth in trade associations since the reform and “opening-up” in 1978. We analyze public policies pertaining to trade associations, survey data collected from 212 local trade associations in Shanghai, and interviews of government officials and trade association leaders. The research results show that trade associations are significantly less dependent on the government and they seem to be more oriented to providing services for and representing corporate members. We trace these changes to public policy reforms and growth in private businesses. The transition reflects the dynamic and changing relationship among the government, trade associations, and business in China. We conclude with a model of these dynamics and a discussion of the implications of this study.

Shock-tube experiments are conducted to investigate the Atwood-number dependence of hydrodynamic instability induced by a strong shock with a Mach number exceeding 3.0. The compressible linear theory performs reliably under varying compressibility conditions. In contrast, the impulsive model significantly loses predictive accuracy at high shock intensities and Atwood numbers ($A_t$), particularly when specific heat ratio differences across the interface are pronounced. To address this limitation, we propose a modified impulsive model that offers favourable predictions over a wide range of compressibility conditions while retaining practical simplicity. In the nonlinear regime, increasing $A_t$ enhances both the shock-proximity and secondary-compression effects, which suppress bubble growth at early and late stages, respectively. Meanwhile, spike growth is promoted by the spike-acceleration and shock-proximity mechanisms. Several models reproduce spike growth across a wide range of $A_t$, whether physical or incidental. In contrast, no models reliably describe bubble evolution under all $A_t$ conditions, primarily due to neglecting compressibility effects that persist into the nonlinear regime. Building on these insights, we develop an empirical model that effectively captures bubble evolution over a wide $A_t$ range. Modal evolution is further shown to be strongly affected by compressibility-induced variations in interface morphology. The effect is particularly pronounced at moderate to high $A_t$, where it suppresses the fundamental mode growth while promoting higher-order harmonic generation.

Rotary flow focusing (RFF) is distinguished from conventional microfluidic platforms through its capacity to accommodate wide viscosity ranges in both continuous and dispersed phases during droplet formation. The dynamic mechanisms during droplet formation and the parametric dependencies within RFF systems are examined systematically. Four distinct flow modes, including squeezing, dripping, jetting and tip-streaming, are achieved by varying the rotational velocity and the dispersed-phase flow rate, and the corresponding transition boundaries are identified. In the squeezing and dripping modes, scaling laws are derived to predict droplet size based on interfacial dynamics during the breakup of the dispersed phase. In the jetting mode, functional relationships describing how jet diameter, droplet size and jet length depend on flow parameters are established through external flow field analysis. The tip-streaming mode facilitates the production of droplets at very small scale, with the effects of flow control parameters on droplet size quantitatively evaluated. Additionally, the effects of geometric parameters and fluid physical properties on RFF performance are investigated, enabling the successful production of high-viscosity fluid droplets ranging from micrometre to millimetre scales.

This paper reports the methods and preliminary findings of Germina, an ongoing cohort study to identify biomarkers and trajectories of executive functions and language development in the first 3 years of life. 557 mother-infant dyads (mean age of mothers 33.7 years, 65.2% white, 48.7% male infants) have undergone baseline and are currently collecting data for other timepoints. A linear regression was used to predict baseline Bayley-III using scores derived from data-driven sparse partial least squares utilizing a multiple holdout framework of 15 domains. Significant associations were found between socioeconomic/demographic characteristics (B = 0.29), epigenetics (B = 0.11), EEG theta (B = 0.14) and beta activity (B = 0.11), and microbiome functional pathways (B = 0.08) domains, and infant development measured by the Bayley-III at T1, suggesting potential interventions to prevent impairments.

We report the first shock-tube experiments on Richtmyer–Meshkov instability at a single-mode light–heavy interface accelerated by a strong shock wave with Mach number higher than 3.0. Under the proximity effect of the transmitted shock and its induced secondary compression effect, the interface profile is markedly different from that in weakly compressible flows. For the first time, the validity of the compressible linear theory and the failure of the impulsive model in predicting the linear amplitude evolution in highly compressible flows are verified through experiments. Existing nonlinear and modal models fail to accurately describe the perturbation evolution, as they do not account for the shock proximity and secondary compression effects on interface evolution. The shock proximity effect manifests mainly in the early stages when the transmitted shock remains close to the interface, while the effect of secondary compression manifests primarily at the period when interactions of transverse shocks occur at the bubble tips. Based on these findings, we propose an empirical model capable of predicting the bubble evolution in highly compressible flows.

We demonstrate a high-peak-power master oscillator power amplifier burst-mode laser system that generates microsecond burst duration pulses at 355 nm with a GHz-adjustable intra-burst pulse frequency. In the fiber seed, a high-bandwidth electro-optic modulator is employed to modulate a continuous-wave (CW) laser into a pulse train at GHz frequency. To acquire a microsecond rectangular burst pulse envelope, two acousto-optic modulators are used to chop the CW pulse train and generate a pre-compensation burst envelope. A three-stage neodymium-doped yttrium aluminum garnet amplifier boosts the burst-mode fiber seed’s burst energy of 1.65 J at 1064 nm. To achieve a high-power ultraviolet (UV) burst-mode laser, sum frequency generation in a LiB3O5 crystal is employed to convert the wavelength, achieving over 300 kW of peak power at 1.15 μs/10 Hz. The intra-burst pulse frequency of the UV burst laser can be adjustable from 1 to 10 GHz with a sinusoidal waveform. To the best of our knowledge, this paper represents the highest reported microsecond UV burst-mode laser in terms of output energy and peak power with the GHz-adjustable intra-burst frequency. The high-power microsecond UV burst-mode pulse laser can be directly used as a light-driven source in large-bandwidth/high-power microwave photonic systems, providing a long pulse width and high peak power laser while significantly improving the system’s multi-parameter adjustment capability and adaptability.

Maximum likelihood estimation of generalized linear mixed models (GLMMs) is difficult due to marginalization of the random effects. Derivative computations of a fitted GLMM’s likelihood are also difficult, especially because the derivatives are not by-products of popular estimation algorithms. In this paper, we first describe theoretical results related to GLMM derivatives along with a quadrature method to efficiently compute the derivatives, focusing on fitted lme4 models with a single clustering variable. We describe how psychometric results related to item response models are helpful for obtaining the derivatives, as well as for verifying the derivatives’ accuracies. We then provide a tutorial on the many possible uses of these derivatives, including robust standard errors, score tests of fixed effect parameters, and likelihood ratio tests of non-nested models. The derivative computation methods and applications described in the paper are all available in easily obtained R packages.

Measurement invariance is a fundamental assumption in item response theory models, where the relationship between a latent construct (ability) and observed item responses is of interest. Violation of this assumption would render the scale misinterpreted or cause systematic bias against certain groups of persons. While a number of methods have been proposed to detect measurement invariance violations, they typically require advance definition of problematic item parameters and respondent grouping information. However, these pieces of information are typically unknown in practice. As an alternative, this paper focuses on a family of recently proposed tests based on stochastic processes of casewise derivatives of the likelihood function (i.e., scores). These score-based tests only require estimation of the null model (when measurement invariance is assumed to hold), and they have been previously applied in factor-analytic, continuous data contexts as well as in models of the Rasch family. In this paper, we aim to extend these tests to two-parameter item response models, with strong emphasis on pairwise maximum likelihood. The tests’ theoretical background and implementation are detailed, and the tests’ abilities to identify problematic item parameters are studied via simulation. An empirical example illustrating the tests’ use in practice is also provided.