Extant studies on cross-border venture capital (VC) investment predominantly focus on how country-level formal institutions impact the flow of VCs across borders, but the potential role of country-level sentiments in this process has received less attention. Drawing upon the trust literature, we explore how home country political sentiment affects cross-border VC investment. Using data on Chinese VCs’ cross-border investments from 2000 to 2021, we find that home country political sentiment positively affects the amount of cross-border VC investment. Government VC (GVC) and connected VC (through sentiment transmission) positively, while investor managerial team education and investor host country experience (through sentiment suppression) negatively, moderate the influence of home country political sentiment.

We investigate the dynamics of circular self-propelled particles in channel flow, modelled as squirmers using a two-dimensional lattice Boltzmann method. The simulations explore a wide range of parameters, including channel Reynolds numbers ($\textit{Re}_c$), squirmer Reynolds numbers ($\textit{Re}_s$) and squirmer-type factors ($\beta$). For a single squirmer, four motion regimes are identified: oscillatory motion confined to one side of the channel, oscillatory crossing of the channel centreline, stabilisation at a lateral equilibrium position with the squirmer tilted and stable upstream swimming near the channel centreline. For two squirmers, interactions produce not only these four corresponding regimes but also three additional ones: continuous collisions with repeated position exchanges, progressive separation and drifting apart and, most notably, the formation of a stable wedge-like conformation (regime D). A key finding is the emergence of regime D, which predominantly occurs for weak pullers ($\beta = 1$) and at moderate to high $\textit{Re}_c$ values. Hydrodynamic interactions align the squirmers with streamline bifurcations near the channel centreline, enabling stability despite transient oscillations. Additionally, the channel blockage ratio critically affects the range of $\textit{Re}_s$ values over which this regime occurs, highlighting the influence of geometric confinement. This study extends the understanding of squirmer dynamics, revealing how hydrodynamic interactions drive collective behaviours. The findings also offer insights into the design of self-propelled particles for biomedical applications and contribute to the theoretical framework for active matter systems. Future work will investigate three-dimensional effects and the stability conditions for spherical squirmers forming stable wedge-like conformations, further generalising these results.

Multi-loop coupling mechanisms (MCMs) are extensively utilized in the aerospace and aviation industries. This paper analyzes the mobility, singularity, and optimal actuation selection of a 3RR-3RRR MCM on the basis of geometric algebra (GA), where R denotes revolute joint. First, the principle of the shortest path is employed to identify the basic limbs and ascertain the type of coupling limbs. The analytical expression for the twist space and mobility characteristics of the mechanism is obtained by calculating the intersection of the limb’s twist space. The blade of limb constraint is subsequently employed to construct the singular polynomials of the mechanism. The singular configurations of the 3RR-3RRR MCM are analyzed in accordance with the properties of the outer product, resulting in the identification of two distinct types of boundary singularities. Next, the local transmission index is employed to evaluate the motion/force transmission performance of the two actuation schemes and finalize the selection of the superior actuation scheme for the mechanism. Finally, a prototype is developed to evaluate the energy loss resulting from the two actuation schemes, which verifies the correctness of the actuation selection scheme.

Germplasm resources are the foundation for improving crop varieties and a strategic asset for global food security. They also advance plant breeding, agricultural biotechnology and the production of essential agricultural goods. To assess the distribution, diversity and conservation status of food crop germplasm in the Hainan Province, China, we conducted a detailed survey of the Hainan Island. Between 2017 and 2022, we collected 330 food crop germplasm resources, encompassing 16 cereal crops, including rice, maize, sweet potato. The collected germplasm resources exhibited traits of high resistance to both biotic and abiotic stresses, including common diseases and drought stress, as well as superior quality and adaptability to poor soil conditions such as sandy land. However, challenges such as low productivity and hybrid degradation were identified. These resources were primarily found in Haikou City, Baisha County, Danzhou City, Wuzhishan City and Sanya City. Additionally, we collected several ancient local varieties and endangered germplasm resources such as ‘Jiezi rice’ and ‘Wuzhishan maize’. This study serves as a reference for the conservation, development and utilization of local food crop germplasm resources in Hainan Province and lays the foundation for breeding and developing new varieties.

With the widespread use of high-fat diets (HFD) in aquaculture, the adverse effects of HFD on farmed fish are becoming increasingly apparent. Creatine has shown potential as a green feed additive in farmed fish; however, the potential of dietary creatine to attenuate adverse effects caused by high-fat diets remains poorly understood. To address such gaps, this study was conducted to investigate the mitigating effect of dietary creatine on HFD-induced disturbance on growth performance, hepatic lipid metabolism, intestinal health and muscle quality of juvenile largemouth bass. Three diets were formulated: a control diet (10·20 % lipid), a high-fat diet (HFD, 18·31 % lipid) and HFD with 2 % creatine (HFD + creatine). Juvenile largemouth bass (3·73 (sem 0·01) g) were randomly assigned to three diets for 10 weeks. The key findings were as follows: (1) the expression of muscle growth-related genes and proteins was stimulated by dietary creatine, which contributes to ameliorate the adverse effects of HFD on growth performance; (2) dietary creatine alleviates HFD-induced adverse effects on intestinal health by improving intestinal health, which also enhances feed utilisation efficiency; (3) dietary creatine causes excessive lipid deposition, mainly via lipolysis and β-oxidation. Notably, this study also reveals a previously undisclosed effect of creatine supplementation on improving muscle quality. Together, for the first time from a comprehensive multiorgan or tissue perspective, our study provides a feasible approach for developing appropriate nutritional strategies to alleviate the adverse effects of HFD on farmed fish, based on creatine supplementation.

This study presents a novel investigation into the vortex dynamics of flow around a near-wall rectangular cylinder based on direct numerical simulation at $Re=1000$, marking the first in-depth exploration of these phenomena. By varying aspect ratios ($L/D = 5$, $10$, $15$) and gap ratios ($G/D = 0.1$, $0.3$, $0.9$), the study reveals the vortex dynamics influenced by the near-wall effect, considering the incoming laminar boundary layer flow. Both $L/D$ and $G/D$ significantly influence vortex dynamics, leading to behaviours not observed in previous bluff body flows. As $G/D$ increases, the streamwise scale of the upper leading edge (ULE) recirculation grows, delaying flow reattachment. At smaller $G/D$, lower leading edge (LLE) recirculation is suppressed, with upper Kelvin–Helmholtz vortices merging to form the ULE vortex, followed by instability, differing from conventional flow dynamics. Larger $G/D$ promotes the formation of an LLE shear layer. An intriguing finding at $L/D = 5$ and $G/D = 0.1$ is the backward flow of fluid from the downstream region to the upper side of the cylinder. At $G/D = 0.3$, double-trailing-edge vortices emerge for larger $L/D$, with two distinct flow behaviours associated with two interactions between gap flow and wall recirculation. These interactions lead to different multiple flow separations. For $G/D = 0.9$, the secondary vortex (SV) from the plate wall induces the formation of a tertiary vortex from the lower side of the cylinder. Double-SVs are observed at $L/D = 5$. Frequency locking is observed in most cases, but is suppressed at $L/D = 10$ and $G/D = 0.9$, where competing shedding modes lead to two distinct evolutions of the SV.

The oriental armyworm, Mythimna separata (Walker), is a highly migratory pest known for its sudden larval outbreaks, which result in severe crop losses. These unpredictable surges pose significant challenges for timely and accurate monitoring, as conventional methods are labour-intensive and prone to errors. To address these limitations, this study investigates the use of machine learning for automated and precise identification of M. separata larval instars. A total of 1577 larval images representing different instar were analysed for geometric, colour, and texture features. Additionally, larval weight was predicted using 13 regression models. Instar identification was conducted using Support Vector Classifier (SVC), Random Forest, and Multi-Layer Perceptron. Key feature contributing to classification accuracy were subsequently identified through permutation feature importance analysis. The results demonstrated the potential of machine learning for automating instar identification with high efficiency and accuracy. Predicted larval weight emerged as a key feature, significantly enhancing the performance of all identification models. Among the tested approaches, BaggingRegressor exhibited the best performance for larval weight prediction (R2 = 98.20%, RMSE = 0.2313), while SVC achieved the highest instar identification accuracy (94%). Overall, the integration of larval weight with other image-derived features proved to be a highly effective strategy. This study demonstrates the efficacy of machine learning in enhancing pest monitoring systems by providing a scalable and reliable framework for precise pest management. The proposed methodology significantly improves larval instar identification accuracy and efficiency, offering actionable insights for implementing targeted biological and chemical control strategies.

Coherent combining of several low-energy few-cycle beams offers a reliable and feasible approach to producing few-cycle laser pulses with energies exceeding the multi-joule level. However, time synchronization and carrier-envelope phase difference (ΔCEP) between pulses significantly affect the temporal waveform and intensity of the combined pulse, requiring precise measurement and control. Here, we propose a concise optical method based on the phase retrieval of spectral interference and quadratic function symmetry axis fitting to simultaneously measure the time synchronization and ΔCEP between few-cycle pulses. The control precision of our coherent beam combining system can achieve a time delay stability within 42 as and ΔCEP measurement precision of 40 mrad, enabling a maximum combining efficiency of 98.5%. This method can effectively improve the performance and stability of coherent beam combining systems for few-cycle lasers, which will facilitate the obtaining of high-quality few-cycle lasers with high energy.

This article is concerned with the spreading speed and traveling waves of a lattice prey–predator system with non-local diffusion in a periodic habitat. With the help of an associated scalar lattice equation, we derive the invasion speed for the predator. More specifically, when the dispersal kernel of the predator is exponentially bounded, the invasion speed is finite and can be characterized in terms of principal eigenvalues; while the dispersal kernel is algebraically decaying, the invasion speed is infinite and the accelerated spreading rate is obtained. Furthermore, the existence and non-existence of traveling waves connecting the semi-equilibrium point to a uniformly persistent state are established.

This paper addresses the issue of energy-efficient trajectory optimization for planetary surface manipulators under kinematic and dynamic constraints. To mitigate the inefficiency of existing algorithms, an adaptive boundary adjustment strategy for the multi-dimensional decision space is proposed, which modifies the time intervals between neighboring configuration nodes, enabling precise adaptation of the decision space boundaries. Additionally, a complementary dual-archive guided boundary exploration strategy is introduced to connect the feasible and infeasible regions, allowing for the effective utilization of information from infeasible solutions near the constraint boundaries. This heuristic approach guides the particle swarm in efficiently exploring areas close to the constraints, significantly enhancing the evolutionary optimization capability of the swarm. Furthermore, a swarm optimal position updating strategy based on sparsity sorting is developed. This guides the particle swarm to concentrate on exploring positions where non-dominated solutions on the Pareto front are more sparsely distributed, ensuring uniformity and completeness in the final Pareto front. Finally, the aforementioned strategies are integrated into a heuristic multi-objective particle swarm optimization (HMOPSO) algorithm for the trajectory optimization of manipulators. Comparative experiments are conducted with HMOPSO and existing advanced algorithms in the field of multi-objective optimization. Experimental results demonstrate that HMOPSO exhibits superior evolutionary optimization capabilities and faster convergence rates. Moreover, performance metrics such as inverse generation distance and dominant area during the iterative process of HMOPSO significantly outperform those of existing optimization algorithms.

Optical fibers offer convenient access to a variety of nonlinear phenomena. However, due to their inversion symmetry, second-order nonlinear effects, such as second-harmonic generation (SHG), are challenging to achieve. Here, all-fiber in-core SHG with high beam quality is achieved in a random fiber laser (RFL). The fundamental wave (FW) is generated in the same RFL. The phase-matching condition is mainly achieved through an induced periodic electric field and the gain is enhanced through the passive spatiotemporal gain modulation and the extended fiber. The conversion needs no pretreatment and the average second-harmonic (SH) power reaches up to 10.06 mW, with a corresponding conversion efficiency greater than 0.04%. Moreover, a theoretical model is constructed to explain the mechanism and simulate the evolution of the SH and FW. Our work offers a simple method to generate higher brightness for in-fiber SHs, and may further provide new directions for research on all-fiber χ(2)-based nonlinear fiber optics and RFLs.

While both simultaneous and sequential contests are mechanisms used in practice such as crowdsourcing, job interviews and sports contests, few studies have directly compared their performance. By modeling contests as incomplete information all-pay auctions with linear costs, we analytically and experimentally show that the expected maximum effort is higher in simultaneous contests, in which contestants choose their effort levels independently and simultaneously, than in sequential contests, in which late entrants make their effort choices after observing all prior participants’ choices. Our experimental results also show that efficiency is higher in simultaneous contests than in sequential ones. Sequential contests’ efficiency drops significantly as the number of contestants increases. We also discover that when participants’ ability follows a power distribution, high ability players facing multiple opponents in simultaneous contests tend to under-exert effort, compared to theoretical predictions. We explain this observation using a simple model of overconfidence.