In this paper, a novel series–parallel stable platform is proposed, and its kinematic and dynamic models are established. The relationship between the length, speed, and acceleration of rolling and pitching electric push rods is analyzed. The workspace of the series–parallel stable platform is determined, and the singularity and interference are analyzed. The state-machine-based control system of the stable platform is designed. An experimental environment of the principle of the real-time control system based on dSPACE was built. A position–speed double closed-loop experiment, simulating mounting carrier of the random signal tracking, and system comprehensive performance experiment were conducted to verify the accuracy of the kinematics and dynamics model of the series–parallel stable platform and the rationality and stability of the control system.

We investigate the inertial migration of slender, axisymmetric, neutrally buoyant filaments in planar Poiseuille flow over a wide range of channel Reynolds numbers (${\textit{Re}}_c \in [0.5, 2000]$). Filaments exhibit complex oscillatory trajectories during tumbling, with the lateral migration velocity strongly coupled to their orientation. Using a singular perturbation approach, we derive a quasi-analytical expression for the migration velocity that captures both instantaneous and period-averaged behaviour. Finite-size effects are incorporated through solid-phase inertia and the influence of fluid inertia on the orientation dynamics. To validate the theory, we develop a fully resolved numerical framework based on the lattice Boltzmann and immersed boundary methods. The theoretical predictions show good agreement with simulation results over a wide range of Reynolds numbers and confinement ratios. Our model outperforms previous theories by providing improved agreement in predicting equilibrium positions across the investigated range of ${\textit{Re}}_c$, particularly at high values. Notably, it captures the inward migration trend toward the channel centreline at high ${\textit{Re}}_c$ and reveals a new dynamics, including the cessation and resumption of tumbling under strong inertial effects. These findings provide a robust foundation for understanding filament migration and guiding inertial microfluidic design.

Wall pressure fluctuations (WPFs) over aerodynamic surfaces contribute to the physical origin of noise generation and vibrational loading. Understanding the generation mechanism of WPFs, especially those exhibiting extremely high amplitudes, is important for advancing design and control in practical applications. In this work, we systematically investigate extreme events of WPFs in turbulent boundary layers and the compressibility effects thereon. The compressibility effects, encompassing extrinsic and intrinsic ones, ranging from weak to strong, are achieved by varying Mach numbers and wall temperatures. A series of datasets at moderate Reynolds numbers obtained from direct numerical simulation are analysed. It is found that the intermittency of WPFs depends weakly on extrinsic compressibility effects, whereas intrinsic compressibility effects significantly enhance intermittency at small scales. Coherent structures related to extreme events are identified using volumetric conditional average. Under extrinsic compressibility effects, extreme events are associated with the weak dilatation structures induced by interactions of high- and low-speed motions. When intrinsic compressibility effects dominate, these events are associated with the strong alternating positive and negative dilatation structures embedded in low-speed streaks. Furthermore, Poisson-equation-based pressure decomposition is performed to partition pressure fluctuations into components governed by distinct physical mechanisms. By analysing the proportion of each pressure component in extreme events, it is found that the contributions of the slow pressure and viscous pressure exhibit weak dependence on the compressibility effects, especially the extrinsic ones, and the varying trend of contributions of the rapid pressure with compressibility effects is opposite to that of the compressible pressure component.

Accurate 3D deformation control of deformable soft tissues is of paramount importance in robotic-assisted surgeries. Selecting optimal grasping points is a fundamental challenge, as the deformation behavior is highly dependent on the applied forces and their locations. This paper presents an efficient grasping point selection algorithm using optimization-based inverse finite element method for tissue manipulation tasks. We propose a method for the automatic identification of optimal grasping points that minimize feature or shape errors during deformation tasks. Specifically, we formulate the grasping task as a quadratic programming problem while considering the complex mechanical coupling within the tissue structure. Our method effectively accommodates both discrete key points and point clouds as input, and can simultaneously determine multiple optimal grasping points in one optimization process. We validate the proposed method in simulation on a tissue and liver model, demonstrating its feasibility and efficiency in various scenarios. Real-world experiments are conducted on a silicone liver phantom to further validate the effectiveness of our proposed method.

The emergence, on the Loess Plateau of Central China, of settlements enclosed by circular ditches has engendered lively debate about the function of these (often extensive) ditch systems. Here, the authors report on a suite of new dates and sedimentological analyses from the late Yangshao (5300–4800 BP) triple-ditch system at the Shuanghuaishu site, Henan Province. Exploitation of natural topographic variations, and evidence for ditch maintenance and varied water flows, suggests a key function in hydrological management, while temporal overlap in the use of these three ditches reveals the large scale of this endeavour to adapt to the pressures of the natural environment.

The study presents a novel cable-driven serial robot based on flexible joints and tensegrity structures, which features a rapid response capability in complex dynamic environments. This makes it particularly suitable for human–robot interaction scenarios. Compared to traditional rigid serial robots, the design’s compliance demonstrates significant advantages in addressing complex demands. The study delves into kinematic and dynamic modeling methods and verifies their effectiveness through simulations. The kinematic model transforms the local coordinate system to the global one using general kinematic equations. First, the static and dynamic model of the robot is derived based on the torque balance equation, and then the dynamic model of the robot is constructed. By simplifying the robot model, the relationship between tension values from driving cables and the robot’s workspace is analyzed under the constraints of tensegrity structures and flexible joints. Additionally, trajectory simulations validate the kinematic and dynamic models. The kinetic energy variation curves based on the trajectories confirm the accuracy of the theoretical analysis. This method demonstrates broad applicability and can be applied to other serial robots with flexible structures, offering effective solutions for use in complex dynamic environments.

Saccharum barberi is regarded as a sugarcane germ plasm resource of potential value. Tissue culture serves multiple purposes in breeding-related research for sugarcane. The response to tissue culture varies considerably among sugarcane genotypes; however, the influence of genetic differences on the tissue culture performance of S. barberi had not been previously investigated. This study evaluated the genotypic variation in tissue culture response among six accessions of S. barberi. Seven parameters were assessed to determine the tissue culture performance: callus induction frequency (CIF), embryogenic callus ratio, embryogenic callus induction frequency, callus regeneration frequency, callus regeneration coefficient, overall regeneration frequency (ORF) and overall regeneration coefficient (ORC). Significant variations (P < 0.05) were observed among the S. barberi genotypes for all parameters. The broad-sense heritability ranged from 80.77% to 93.10%, indicating that genetic differences were the primary source of genotypic variation. ORF exhibited the highest diversity among the parameters, with a genotypic coefficient of variation up to 70.06%. Pansahi was identified as the most amenable genotype to tissue culture, demonstrating superior performance in both callus induction and plant regeneration. CIFs at different induction periods were strongly positively correlated with both ORF and ORC, particularly during the first week, suggesting that CIF may serve as a promising early predictor of overall regeneration competence. This study is the first to report the effect of genotypic variation on callus induction and plant regeneration of S. barberi, and the findings will be valuable for future research involving tissue culture in this species.

Selecting appropriate texts for second language (L2) learners is essential for effective education. However, current text difficulty models often inadequately classify materials for L2 learners by proficiency levels. This study addresses this deficiency by employing the Common European Framework of Reference for Languages (CEFR) as its foundational framework. A cohort of expert English-L2 educators classified 1,181 texts from the CommonLit Ease of Readability corpus into CEFR levels. A random forest model was then trained using 24 linguistic complexity features to predict the CEFR levels of English texts for L2 learners. The model achieved 62.6% exact-level accuracy across the six granular CEFR levels and 82.6% across the three overarching levels, outperforming a baseline model based on three existing readability formulas. Additionally, it identified shared and unique linguistic features across different CEFR levels, highlighting the necessity to adjust text classification models to accommodate the distinct linguistic profiles of low- and high-proficiency readers.

Several million years of natural evolution have endowed marine animals with high flexibility and mobility. A key factor in this achievement is their ability to modulate stiffness during swimming. However, an unresolved puzzle remains regarding how muscles modulate stiffness, and the implications of this capability for achieving high swimming efficiency. Inspired by this, we proposed a self-propulsor model that employs a parabolic stiffness-tuning strategy, emulating the muscle tensioning observed in biological counterparts. Furthermore, efforts have been directed towards developing the nonlinear vortex sheet method, specifically designed to address nonlinear fluid–structure coupling problems. This work aims to analyse how and why nonlinear tunable stiffness influences swimming performance. Numerical results demonstrate that swimmers with nonlinear tunable stiffness can double their speed and efficiency across nearly the entire frequency range. Additionally, our findings reveal that high-efficiency biomimetic propulsion originates from snap-through instability, which facilitates the emergence of quasi-quadrilateral swimming patterns and enhances vortex strength. Moreover, this study examines the influence of nonlinear stiffness on swimming performance, providing valuable insights into the optimisation of next-generation, high-performance, fish-inspired robotic systems.

Tuberculosis (TB) remains a significant public health concern in China. Using data from the Global Burden of Disease (GBD) study 2021, we analyzed trends in age-standardized incidence rate (ASIR), prevalence rate (ASPR), mortality rate (ASMR), and disability-adjusted life years (DALYs) for TB from 1990 to 2021. Over this period, HIV-negative TB showed a marked decline in ASIR (AAPC = −2.34%, 95% CI: −2.39, −2.28) and ASMR (AAPC = −0.56%, 95% CI: −0.62, −0.59). Specifically, drug-susceptible TB (DS-TB) showed reductions in both ASIR and ASMR, while multidrug-resistant TB (MDR-TB) showed slight decreases. Conversely, extensively drug-resistant TB (XDR-TB) exhibited upward trends in both ASIR and ASMR. TB co-infected with HIV (HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB) showed increasing trends in recent years. The analysis also found an inverse correlation between ASIRs and ASMRs for HIV-negative TB and the Socio-Demographic Index (SDI). Projections from 2022 to 2035 suggest continued increases in ASIR and ASMR for XDR-TB, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB. The rising burden of XDR-TB and HIV-TB co-infections presents ongoing challenges for TB control in China. Targeted prevention and control strategies are urgently needed to mitigate this burden and further reduce TB-related morbidity and mortality.