Previous studies have indicated that Eno1 may play an important role in Cadmium (Cd) resistance. However, the potential regulatory mechanisms of Eno1 in response to Cd2+ stress are still limited. In this study, we hypothesised that Cd-induced miRNA alteration could effectively regulate PaEno1 (Eno1 in Propsilocerus akamusi (Diptera: Chironomidae)) under Cd2+ stress. By integrating Illumina miRNA sequencing, real-time quantitative Polymerase chain reaction (PCR) (RT-qPCR) validation, PaEno1 target prediction and in vivo functional assays, we verified that PaEno1 is a putative target of miR-92a and miR-279d, which potentially mediate the post-transcriptional regulation of PaEno1 under Cd2⁺ stress. RT-qPCR revealed significant downregulation of miR-92a and miR-279d by 2.825–4.225-fold upon long-term Cd exposure. Agomir/antagomir-mediated overexpression and knockdown of the two miRNAs exerted no significant impact on larval survival (Log-rank test, p > 0.05). The hazard ratios were 0.715 and 0.609 for miR-279d (agomir and antagomir), and 0.810 and 0.869 for miR-92a, respectively. The 95% confidence intervals spanned 0.266–1.921 and 0.217–1.712 for miR-279d agomir and antagomir, and 0.399–1.642 and 0.434–1.740 for miR-92a agomir and antagomir, with all intervals crossing the null value of 1. Agomir-induced upregulation of miR-92a and miR-279d dynamically altered the expression of PaEno1, HbV, HbVII, alpha-esterase, and carboxylesterase. Overall, miR-92a and miR-279d act as temporal post-transcriptional regulators of PaEno1 rather than key modulators of Cd tolerance. This work underscores the complexity of miRNA-regulated networks in P. akamusi responding to Cd stress.

This study examined the development of bilingual lexical networks in adolescence through word association task and network analysis. Participants were Chinese–English bilinguals in Grade 8 (middle school; aged 13–14 years) and Grade 11 (high school; aged 16–17 years). Networks were constructed based on word association responses separately for each grade and language, and structural properties of networks were computed. Results showed that from Grade 8 to Grade 11, the Chinese networks displayed increased within-group convergence while maintaining overall structural stability and small-world features. In contrast, the English networks expanded in size, with longer average shortest paths, higher local clustering, and greater modularity (Q), reflecting rapid growth and restructuring, while also exhibiting small-world features. Across grades, L1 networks remained larger and more structured than L2 networks, though the gap decreased over time, indicating increasing cross-language similarity. These findings provide new insights into bilingual lexical development during the adolescent years.

We perform numerical simulations of forced homogeneous isotropic turbulence over a range of bulk viscosities, Reynolds numbers and Mach numbers to investigate the scaling of key flow statistics. Using the Helmholtz decomposition, we analyse the scalings of Favre-averaged turbulent kinetic energy (TKE), root-mean-square (r.m.s.) pressure, pressure dilatation, dilatational dissipation and higher-order velocity-gradient moments. Additionally, new models are proposed for the pressure-dilatation term and the bulk-viscosity dependence of dilatational dissipation. Although the solenoidal and dilatational components of the Favre-averaged TKE are not strictly orthogonal, our numerical results demonstrate that their ratio is well approximated by the squared ratio of the corresponding r.m.s. velocities. The r.m.s. pressure approaches the pseudo-sound scaling as bulk viscosity increases. Within the Donzis r.m.s. pressure model (Donzis & John 2020 Phys. Rev. Fluids 5(8), 084609), we find that the solenoidal contribution becomes dominant for large bulk viscosity. Pressure dilatation is found to depart systematically from pseudo-sound predictions: without bulk viscosity it favours transfer from kinetic to internal energy, while finite bulk viscosity can reverse this transfer at high Mach numbers. The scaling exponent of dilatational dissipation is shown to vary with bulk viscosity, enabling a corrected model for its exponent and prefactor. Velocity-gradient skewness and flatness reveal that the onset of shocklet-induced divergence is delayed with increasing bulk viscosity and may be suppressed entirely. The results extend recent velocity-ratio-based scaling frameworks and provide modelling insights into compressible turbulence.

Maternal Hb and fetal growth change dynamically throughout pregnancy. We examined the associations of time-specific Hb levels and Hb trajectories with fetal biometrics and adverse birth outcomes. This prospective study included 6844 pregnant women (mean age 26·6 (sd 3·7) years) from the Tongji-Huaxi-Shuangliu Birth Cohort. Hb levels were measured at four periods: early (6–12 gestational weeks), middle (13–27), middle-late (28–32) and late pregnancy (33–37). Fetal biometrics were assessed by ultrasound from middle to late pregnancy. Birth outcomes were obtained from medical records, including small for gestational age (SGA), low birth weight (LBW) and preterm birth. Three Hb trajectories were identified: consistent decline (Trajectory 1), consistently low (Trajectory 2) and increase from middle-late pregnancy (Trajectory 3). Compared with Trajectory 1, Trajectory 3 was associated with lower estimated fetal weight (β, −0·54; 95 % CI −0·99, −0·09) and abdominal circumference (β, −0·21; 95 % CI −0·40, −0·01) in late pregnancy and higher umbilical artery resistance index across pregnancy (β, 0·65; 95 % CI 0·31, 1·00). Trajectory 3 was also associated with higher risk of LBW (OR, 1·57; 95 % CI 1·09, 2·26). In middle-late pregnancy, higher Hb (≥ 130 g/l) was associated with higher risks of LBW (OR, 2·26; 95 % CI 1·08, 4·25) and preterm birth (OR, 2·03; 95 % CI 1·12, 3·44) compared with the reference (110–129 g/l). Elevated maternal Hb from middle-late pregnancy onwards may be associated with lower fetal weight and increased risk of LBW. Dynamic monitoring of maternal Hb may facilitate targeted nutritional management in pregnant women.

The present paper originates from the need to understand nonlinear wave behaviour in dusty plasmas, aiming to explore stable envelope wave propagation and interactions beyond traditional theoretical models. By using nonlinear Schrödinger equation (NLSE) analysis and molecular dynamics (MD) simulations, the study verifies the existence and stable propagation of non-standard envelope waves. It demonstrates elastic like collisions, introduces tuneable parameters for wave shaping and quantifies error trends with nonlinearity. A key breakthrough is confirming that even analytically invalid waveforms remain stable, challenging NLSE constraints. Present results enhance nonlinear wave theory and support precise, tuneable signal transmission in plasma diagnostics and microgravity experiments.

Deep learning (DL) has been applied to phase control in coherent beam combining (CBC) recently. However, existing DL-based approaches for filled-aperture CBC essentially convert the phase-locking path into tiled-aperture schemes. Consequently, common-path phase locking in DL-based filled-aperture CBC remains unrealized. Common-path refers to a phase-locking scheme in which the phase information is extracted from the combined beam after the same combining system. In this paper, a common-path phase-locking method is proposed. By exploiting the intrinsic nonuniformity, each laser source is effectively labeled, enabling a mapping between the combined speckle and the multi-source phase. A neural network is employed to reconstruct the phase. Simulations with 25-channel CBC demonstrate a phase-locking accuracy of up to λ/39. Notably, it remains effective under dynamic phase disturbances. Our work presents a common-path phase-locking approach based on a neural network for filled-aperture CBC, which can offer a new solution for the field.

Bubble dynamics constitutes a fundamental scientific problem in fluid mechanics. Although the oscillation can be predicted through theories for bubble dynamics in previous studies, the viscous effects on the bubble migration remains difficult to predict accurately. In this study, we establish a theoretical model for bubble migration across the entire cycle. The theoretical model derives a drag coefficient expression under dynamic Reynolds numbers, and incorporates corrections to account for non-spherical bubble dynamics. A key advance is the capability to account for viscous drag without relying on constant empirical drag coefficients. Validation against experimental results demonstrates that the theoretical model effectively predicts the bubble migration. Furthermore, we discuss the correlation between drag coefficient and Reynolds number, and elucidate the effects of viscous domain range and bubble deformation on the drag coefficient of the present model.

To investigate how polymers influence energy transfer in three-dimensional turbulence, we conduct experiments in homogeneous bulk turbulence generated by a von Kármán swirling flow, using tomographic particle image velocimetry. A filtering approach is applied to the measured three-dimensional velocity fields to extract subgrid-scale (SGS) statistics, focusing on the filtered strain-rate tensor and SGS stress tensor. We find that polymer additives induce significant changes in the tensorial geometry: the strain-rate tensor shows a tendency towards an eigenvalue ratio of $1 : 0 : -1$, while the SGS stress tensor favours a $2 : -1 : -1$ configuration. The local energy flux – quantified by the inner product of the strain-rate and SGS stress tensors – is systematically suppressed by polymers and becomes increasingly intermittent. This suppression is linked to a reduced energy transfer efficiency, associated with the misalignment between the principal eigendirections of the two tensors. Anisotropic effects are also observed in the energy flux components, indicating that polymers affect vertical and horizontal energy transfer differently. Finally, the obtained SGS statistics allow for an a priori assessment of SGS models. Our results reveal that the nonlinear gradient model significantly outperforms the Smagorinsky model, particularly in polymer-laden turbulence. The diminished alignment between the strain-rate and SGS stress tensors may underlie the limitations of the Smagorinsky model, which assumes a scalar eddy-viscosity closure. These results provide new experimental insights into the SGS dynamics of polymeric turbulence and highlight the potential of nonlinear models for large-eddy simulations of viscoelastic flows.

Legged robots operating in irregular environments are often subjected to compound disturbances such as tilts and vibrations, which can degrade attitude stability and motion reliability. This paper presents a real-time disturbance-adaptive control framework for a hexapod robot. The proposed system integrates quaternion-based attitude estimation using an extended Kalman filter (EKF), a double-threshold pose classifier, and a modular gait library and is implemented on an embedded controller with a 2 ms control-loop latency. Analytical verification and laboratory experiments demonstrate that the proposed control loop achieves uniform ultimate boundedness (UUB) under deterministic hybrid disturbances composed of controlled tilt and vibration, with a mean recovery time of 5.7 s. These results demonstrate that a lightweight rule-based controller can ensure reliable posture recovery within the experimentally validated laboratory scenarios, providing a foundation for future extensions to more complex environments. The main contributions of this work are (1) a disturbance-adaptive gait selection architecture for quasi-static stabilization, (2) a noise-robust EKF-based attitude estimation and double-threshold pose determination scheme, and (3) a concise Lyapunov-based stability analysis demonstrating UUB of the closed-loop system.

This study uses a coupled lattice Boltzmann and discrete element method to perform interface-resolved simulations of turbulent channel flow laden with finite-size cylindrical particles. The aim is to investigate interactions between wall-bounded turbulence and non-spherical particles with sharp edges. The particle-to-fluid density ratio is unity and gravity is neglected. Comparative analyses are conducted among long (length-to-diameter aspect ratio 2), unit (1) and short ($ 1/2 $) cylinders, along with spheres and literature data for spheroids. Results reveal both shared and distinct dynamic behaviours of cylinders and their effects on turbulence modulation. Notably, disk-like short cylinders can remain trapped near the wall due to their flat faces aligning closely with it – a behaviour unique to particles with sharp edges. Long and unit cylinders, as well as spheres, preferentially accumulate in high-speed streaks, while short cylinders cluster in low-speed streaks, demonstrating a strong aspect-ratio effect. Near the wall, long cylinders align their axis with the streamwise direction, while short cylinders orient perpendicular to the wall. Rotationally, long cylinders primarily spin, whereas short ones predominantly tumble. These trends arise from orientation preferences and differences in axial and spanwise moments of inertia. Cylindrical particles increase wall drag compared with the single-phase case, with short cylinders causing the greatest enhancement due to strong near-wall accumulation. Overall, the influence of aspect ratio on particle dynamics and turbulence modulation is more pronounced for cylindrical particles than for spheroidal ones.

Magnetite-enriched mining tailings are a cost-effective and abundant catalytic material with inherent magnetic recyclability. Yet their practical application in catalysis is often constrained by their limited surface area and sluggish reaction kinetics. To address these issues, we developed a facile one-step co-precipitation method to synthesize a magnetic nano-Fe3O4 (MNP) catalyst that exhibits enhanced surface reactivity for efficient activation of H2O2 towards tetracycline (TC) degradation. The system achieved complete (100%) removal of TC at an initial concentration of 20 mg L–1 within 90 min and demonstrated robust catalytic performance across weakly acidic to neutral pH conditions. Mechanistic investigations confirmed that ⋅OH is the primary reactive oxygen species involved, with ⋅O2⁻ and 1O2 providing supplementary contributions to the degradation. Remarkably, the intrinsic magnetic properties ensured efficient MNP catalyst recovery. This work provides a sustainable and scalable wastewater treatment strategy, leveraging mining tailings as a cost-effective resource to treat wastewater while also providing economic and environmental benefits.

Investigations into the effects of polymers on small-scale statistics and flow patterns were conducted in a turbulent von Kármán swirling (VKS) flow. We employed the tomographic particle image velocimetry technique to obtain full information on three-dimensional velocity data, allowing us to effectively resolve dissipation scales. Under varying Reynolds numbers ($R_\lambda =168{-}235$) and polymer concentrations ($\phi =0{-}25\ {\textrm{ppm}}$), we measured the velocity gradient tensor (VGT) and related quantities. Our findings reveal that the ensemble average and probability density function (PDF) of VGT invariants, which represent turbulent dissipation and enstrophy along with their generation terms, are suppressed as polymer concentration increases. Notably, the joint PDFs of the invariants of VGT, which characterise local flow patterns, exhibited significant changes. Specifically, the third-order invariants, especially the local vortex stretching, are greatly suppressed, and strong events of dissipation and enstrophy coexist in space. The local flow pattern tends to be two-dimensional, where the eigenvalues of the rate-of-strain tensor satisfy a ratio $1:0:-1$, and the vorticity aligns with the intermediate eigenvector of the rate-of-strain tensor, while it is perpendicular to the other two. We find that these statistics observations can be well described by the vortex sheet model. Moreover, we find that these vortex sheet structures align with the symmetry axis of the VKS system, and orient randomly in the horizontal plane. Further investigation, including flow visualisation and conditional statistics on vorticity, confirms the presence of vortex sheet structures in turbulent flows with polymer additions. Our results establish a link between single-point statistics and small-scale flow topology, shedding light on the previously overlooked small-scale structures in polymeric turbulence.

Excessive car ownership in cities has led to issues including congestion, air pollution and resource consumption. This paper investigates the impact of rail transit openings on automobile purchases in China based on detailed car sales data during 2013–2015 and using two-way fixed effects panel models. Our study reveals an average decrease of 2.27 per cent in car sales due to rail transit openings. Further analyses of cars with different fuel economy reveal stronger effects on fuel-efficient cars, indicating larger substitution elasticity between public transportation and driving for people with less income. Results also show the negative impact of rail transit openings is larger in cities with more developed economies, higher public revenue, larger population, bigger area and fewer buses. The decline in car sales translates into savings of 7.9 billion liters of gasoline and a reduction of about 20.3 million tons in life-cycle carbon emissions.