A species’ choice of habitat critically influences its survival and reproductive success. Quantifying these preferences reveals key ecological requirements and underpins evidence-based conservation planning. The Temminck’s Tragopan Tragopan temminckii, a protected pheasant species inhabiting mountainous forests in China, exhibits distinct habitat requirements during winter. This study investigated its winter habitat use in replanted broadleaf forests within the Laojunshan Nature Reserve, Sichuan, from December 2024 to February 2025, with the aim of identifying key habitat features. The results showed that T. temminckii selected winter habitats at elevations between 1,310 and 1,860 m, on slopes averaging approximately 24°, predominantly on shady and semi-shady aspects, and in close proximity to streams. The birds preferred sites with taller trees, higher tree and bamboo canopy cover, and greater litter coverage compared with random sites. In contrast, they avoided areas with dense shrub cover and greater herb height, likely as a strategy to reduce predation risk, because dense shrub cover and tall herb constrain visibility and movement. These patterns suggest that tragopans prioritise thermal shelter, foraging efficiency and visual concealment from predators during winter. We suggest that the conservation and restoration of successional broadleaf forests with moderate canopy cover and open understorey conditions would benefit the winter survival and population persistence of this species.

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.

Virtual reality (VR) is a transformative technology for studying language processing and learning. It offers realistic and naturalistic environments while maintaining experimental control, supporting the exploration of social and sensorimotor cues that have often been overlooked in traditional psycholinguistic research. It can also be integrated with behavioral and neurocognitive measures to examine how learning processes influence learning outcomes. These VR characteristics have brought new opportunities and contributed to the expansion of theoretical frameworks on language processing and learning. Through reviewing recent empirical findings, we establish VR as a novel methodology for investigating how embodied and social experiences shape language processing and learning. We emphasize that realizing this potential fully requires real-time multimodal tracking of learning processes, systematic examination of individual differences and development of richer virtual environments and VR-suitable assessment tasks. This review provides methodological insights for future VR research on the neurocognitive bases of language processing and learning.

The investigation of the weathering and alteration of phyllosilicate minerals is crucial for understanding chemical cycles, soil development and environmental fluctuations on the Earth’s surface. This study employs phlogopite extracted from Yuli County, Xinjiang, due to its property of transforming easily into interstratified phlogopite-vermiculite or vermiculite under an acidic oxidizing environment. The preparation of vermiculite is governed by the anion type, pH, oxidizing environment, reaction time and other related factors. Advanced analytical and characterization techniques, such as X-ray powder diffraction, thermogravimetric analysis, differential scanning calorimetry, Fourier-transform infrared spectroscopy, scanning electron microscopy, inductively coupled plasma spectroscopy and X-ray fluorescence were employed to study the phase, spectral characteristics, thermal behaviour, microstructure and compositional modifications of the product before, during and after conversion. The compositional variations before, during and after conversion were also examined. Phlogopite can be converted to vermiculite with the assistance of sulfate and chloride ions under acidic oxidation conditions. Moreover, a higher concentration of SO42– in solutions resulted in elevated SO42– adsorption on the surface of phlogopite in comparison to solutions with Cl–. This accelerates the destruction of the tetrahedra and octahedra in phlogopite, resulting in the release of additional ions (Si4+,Al3+, K+, Mg2+) from the phlogopite framework. This ultimately speeds up the conversion of phlogopite to vermiculite.

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.

The classification of the species in the genus Actias Leach, 1815 (Lepidoptera: Saturniidae) is challenging because many species have a highly similar morphology, while differences in database classification standards also provoke identification problems. To help resolve these issues, we conducted an integrative analysis of 741 cytochrome oxidase subunit I (COI) barcode sequences available by combining phylogenetic reconstruction, population genetic (Fst) metrics, and biogeographic data. This approach delineated 44 molecular operational taxonomic units (MOTUs) and established a genus-specific, empirical genetic distance threshold of 2.05% from a baseline of 29 morphologically validated MOTUs. These 29 MOTUs/morphospecies were then utilized to assess the interspecific genetic distance gap of this genus and further used as the species-level genetic distance to delimit the remaining morphospecies. Applying this multi-evidence framework allowed us to propose a significant re-evaluation of species boundaries, including several taxonomic reclassifications, and to generate the molecular inventory for Actias. Our study illustrates the power of an integrated molecular approach to resolve complex taxonomic issues and provides a robust, data-driven foundation for future research on Actias.

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.

Unmanned aerial vehicles (UAVs) tracking one moving target in an oilfield environment with dynamic obstacles has been studied. Firstly, the UAV tracking one target is modeled mathematically, including the oilfield environment, the UAV kinematic model, the moving target model and so on. Considering the oilfield environment with dynamic obstacles, the chance-constraint method is incorporated into the distributed model predictive control (DMPC) to realise the target tracking and avoid the obstacles in the environment. Secondly, to obtain high-quality control-input sequences, the improved salp swarm algorithm (ISSA) is designed as the solver for the chance-constraint DMPC, integrating the sine-tent-cosine chaotic mapping in the initialisation, the differential mutation operation in the leader-position updating and the nonlinear adaptive inertia weights in the follower-position updating. Finally, the simulation results show that the proposed method has great performance in tracking the moving target in an oilfield environment with dynamic obstacles.

This paper investigates the flow past a flexible splitter plate attached to the rear of a fixed circular cylinder at low Reynolds number 150. A systematic exploration of the plate length ($L/D$), flexibility coefficient ($S^{*}$) and mass ratio ($m^{*}$) reveals new laws and phenomena. The large-amplitude vibration of the structure is attributed to a resonance phenomenon induced by fluid–structure interaction. The modal decomposition indicates that resonance arises from the coupling between the first and second structural modes, where the excitation of the second structural mode plays a critical role. Due to the combined effects of added mass and periodic stiffness variations, the two modes become synchronised, oscillating at the same frequency while maintaining fixed phase difference $\pi /2$. This further results in the resonant frequency being locked at half of the second natural frequency, which is approximately three times the first natural frequency. A reduction in plate length and an increase in mass ratio are both associated with a narrower resonant locking range, while a higher mass ratio also shifts this range towards lower frequencies. A symmetry-breaking bifurcation is observed for cases with $L/D\leqslant 3.5$, whereas for $L/D=4.0$, the flow remains in a steady state with a stationary splitter plate prior to the onset of resonance. For cases with a short flexible plate and a high mass ratio, the shortened resonance interval causes the plate to return to the symmetry-breaking stage after resonance, gradually approaching an equilibrium position determined by the flow field characteristics at high flexibility coefficients.

Team innovation is nurtured by the combination of team members’ diverse knowledge and collaborative teamwork. Previous research predominantly assumed a linear interaction between knowledge diversity and network density in predicting team innovation. A pivotal question arises: How do varying levels of knowledge diversity and network density interact to influence team innovation? To address this complex question, we conducted a machine-learning inductive study, leveraging its ability to uncover curvilinear interactive patterns between knowledge diversity and network density in fostering team innovation. We collected comprehensive, multisource data from 1,883 teams within a prominent high-technology firm in China over a four-year period from 2014 to 2017. The results indicate that knowledge diversity and network density exhibit a curvilinear interactive effect on team innovation. The two factors reinforce each other in the initial stage and foster peak innovation with an optimal balance at a medium-to-high level. Beyond this threshold, however, the two factors begin to restrain each other’s effectiveness. Consistent with the perspective of yin-yang balancing, this study deepens our understanding of the paradoxical joint effects of knowledge diversity and network density on team innovation.

Congenital junctional ectopic tachycardia is a rare arrhythmia that poses significant management challenges. This report presents a case of neonatal-onset congenital junctional ectopic tachycardia treated with cedilanid, amiodarone, and propafenone but persisted in episodes. Sinus rhythm was restored following the initiation of ivabradine therapy. The review of the literature indicates that ivabradine demonstrates efficacy in the treatment of paediatric junctional ectopic tachycardia, particularly in refractory cases, without significant side effects. These findings suggest that ivabradine has broad applications in the treatment of refractory arrhythmias.