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.

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.

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.

The whitefly, Bemisia tabaci is a cryptic species complex in which one member, Middle East-Asia Minor 1 (MEAM1) has invaded globally. After invading large countries like Australia, China, and the USA, MEAM1 spread rapidly across each country. In contrast, our analysis of MEAM1 in India showed a very different pattern. Despite the detection of MEAM1 being contemporaneous with invasions in Australia, the USA, and China, MEAM1 has not spread widely and instead remains restricted to the southern regions. An assessment of Indian MEAM1 genetic diversity showed a level of diversity equivalent to that found in its presumed home range and significantly higher than that expected across the invaded range. The high level of diversity and restricted distribution raises the prospect that its home range extends into India. Similarly, while the levels of diversity in Australia and the USA conformed to that expected for the invaded range, China did not. It suggests that China may also be part of its home range. We also observed that diversity across the invaded range was primarily accounted for by a single haplotype, Hap1, which accounted for 79.8% of all records. It was only the invasion of Hap1 that enabled outbreaks to occur and MEAM1’s discovery.

The Early-Middle Jurassic impression/compression macroflora and the palynoflora from the Qaidam Basin in the northeastern Qinghai-Xizang (Tibetan) Plateau have been well studied; however, fossil wood from this region has not been previously documented systematically. Here, we describe an anatomically well-preserved fossil wood specimen from the Lower Jurassic Huoshaoshan Formation at the Dameigou section in northern Qinghai Province, northwestern China. This fossil exhibits typical Metapodocarpoxylon Dupéron-Laudoueneix et Pons anatomy with usually araucarian radial tracheid pits and variable cross-field pits, representing a new record for Metapodocarpoxylon in the Qaidam Basin. This discovery indicates that trees with this type of wood anatomy were not confined to northern Gondwana but also grew in more northerly regions in Laurasia. The wood displays distinct growth rings, with abundant, well-formed earlywood and narrow latewood. This observation, along with previous interpretations based on macroflora, palynoflora and sedimentological data, suggests that a warm and humid climate with mild seasonality prevailed in the region during the Early Jurassic.

Substantial changes resulting from the interaction of environmental and dietary factors contribute to an increased risk of obesity, while their specific associations with obesity remain unclear. We identified inflammation-related dietary patterns (DP) and explored their associations with obesity among urbanised Tibetan adults under significant environmental and dietary changes. Totally, 1826 subjects from the suburbs of Golmud City were enrolled in an open cohort study, of which 514 were followed up. Height, weight and waist circumference were used to define overweight and obesity. DP were derived using reduced rank regression with forty-one food groups as predictors and high-sensitivity C-reactive protein and prognostic nutritional index as inflammatory response variables. Altitude was classified as high or ultra-high. Two DP were extracted. DP-1 was characterised by having high consumptions of sugar-sweetened beverages, savoury snacks, and poultry and a low intake of tsamba. DP-2 had high intakes of poultry, pork, animal offal, and fruits and a low intake of butter tea. Participants in the highest tertiles (T3) of DP had increased risks of overweight and obesity (DP-1: OR = 1·37, 95 % CI 1·07, 1·77; DP-2: OR = 1·48, 95 % CI 1·18, 1·85) than those in the lowest tertiles (T1). Participants in T3 of DP-2 had an increased risk of central obesity (OR = 2·25, 95 % CI 1·49, 3·39) than those in T1. The positive association of DP-1 with overweight and obesity was only significant at high altitudes, while no similar effect was observed for DP-2. Inflammation-related DP were associated with increased risks of overweight and/or obesity.

Laser-driven inertial confinement fusion (ICF) diagnostics play a crucial role in understanding the complex physical processes governing ICF and enabling ignition. During the ICF process, the interaction between the high-power laser and ablation material leads to the formation of a plasma critical surface, which reflects a significant portion of the driving laser, reducing the efficiency of laser energy conversion into implosive kinetic energy. Effective diagnostic methods for the critical surface remain elusive. In this work, we propose a novel optical diagnostic approach to investigate the plasma critical surface. This method has been experimentally validated, providing new insights into the critical surface morphology and dynamics. This advancement represents a significant step forward in ICF diagnostic capabilities, with the potential to inform strategies for enhancing the uniformity of the driving laser and target surface, ultimately improving the efficiency of converting laser energy into implosion kinetic energy and enabling ignition.

The multi-colour complete light curves and low-resolution spectra of two short period eclipsing Am binaries V404 Aur and GW Gem are presented. The stellar atmospheric parameters of the primary stars were derived through the spectra fitting. The observed and TESS-based light curves of them were analysed by using the Wilson-Devinney code. The photometric solutions suggest that both V404 Aur and GW Gem are semi-detached systems with the secondary component filling its critical Roche Lobe, while the former should be a marginal contact binary. The $O-C$ analysis found that the period of V404 Aur is decreasing at a rate of $dP/dt=-1.06(\pm0.01)\times 10^{-7}\,\mathrm{d}\,\mathrm{ yr}^{-1}$, while the period of GW Gem is increasing at $dP/dt=+2.41(\pm0.01)\times 10^{-8} \mathrm{d}\,\mathrm{yr}^{-1}$. The period decrease of V404 Aur may mainly be caused by the combined effects of the angular momentum loss (AML) via an enhanced stellar wind of the more evolved secondary star and mass transfer between two components. The period increase of GW Gem supports the mass transfer from the secondary to the primary. Both targets may be in the broken contact stage predicted by the thermal relaxation oscillations theory and will eventually evolve to the contact stage. We have collected about 54 well-known eclipsing Am binaries with absolute parameters from the literature. The relations of these parameters are summarised. There are some components that have a higher degree of evolution. The majority of their hydrogen shell may have been stripped away and the stellar internal layer exposed. The accretion processes from such evolved components may be very important for the formation of Am peculiarity in binaries.