Neuropsychiatric disorders (NPDs) are a leading cause of disability worldwide. The predominantly plant-based EAT–Lancet diet has been proposed to confer neuropsychiatric benefits, yet evidence remains limited. This study synthesized associations between adherence to the EAT–Lancet diet and neuropsychiatric outcomes. We searched PubMed, Web of Science, Embase, Scopus, and ProQuest Dissertations and Theses Global through September 4, 2025. Observational studies reporting associations between EAT–Lancet adherence and NPDs were included. Binary outcomes were pooled as hazard ratios (HRs) or odds ratios (ORs), and continuous outcomes as regression coefficients (β). Subgroup, sensitivity, and publication-bias analyses were performed. Certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework (GRADE). Twenty-two cohort and six cross-sectional studies were included. Higher adherence to the EAT–Lancet diet was associated with lower risks of depression (OR 0.76; 95% CI 0.71–0.81), anxiety (OR 0.82; 0.76–0.89), stroke (HR 0.84; 0.76–0.92), and dementia (HR 0.96; 0.93–1.00), whereas no significant association was observed for global cognitive function (β 0.02; −0.01 to 0.06). Sensitivity analyses supported robustness. Certainty of evidence was very low for anxiety, depression, and cognition, and low for stroke and dementia. Greater adherence to the EAT–Lancet diet was associated with lower risks of depression, anxiety, stroke, and dementia. However, given the low certainty of evidence, findings should be interpreted cautiously. Further large prospective studies and randomized controlled trials are warranted to improve evidence quality and clarify the potential role of the EAT–Lancet diet in neuropsychiatric disease prevention.

The canonical scenario of two-degree-of-freedom vortex-induced vibration (VIV) of a circular cylinder is re-examined in this study through high-fidelity large-eddy simulations (LES) at a Reynolds number of 10 000. The in-line and cross-flow vibration amplitudes, frequency responses and hydrodynamic coefficients predicted by the present LES match classical experimental results better than previous numerical attempts. In particular, motivated by an inadequate study yet vital importance of the small-amplitude in-line response in offshore engineering design, we present the first numerical evidence for the existence of three in-line response regions. Furthermore, the present in-line response agrees well with the design guideline DNV-RP-F105. After validating the present results against DNV-RP-F105 and published experiments, the detailed LES datasets enable further analysis of new VIV characteristics and physical mechanisms that have not been explored previously. For example, we identify and explain (i) the existence of twin governing frequencies for several VIV branches with partial synchronisation, (ii) decoupled in-line and cross-flow vibrations in the first in-line branch with symmetric vortex-shedding pattern, where an in-line resonance may not induce a cross-flow resonance, (iii) existence of a new elliptic vibration trajectory for a perfectly in-line resonant condition, (iv) gradualness in the 2S ↔ 2T transition of the vortex-shedding pattern and thus a continuous variation in the vibration amplitudes and hydrodynamic coefficients amid this transition and (v) lowest spanwise correlation of vortex shedding in the super-upper and lower branches, which is induced by complex interactions among ≥4 shed vortices over a cylinder vibration period.

We propose a novel machine-learning-based turbulence closure framework in which a tensor basis neural network (TBNN) is directly embedded into a Reynolds-averaged Navier–Stokes (RANS) formulation, eliminating reliance on traditional baseline turbulence models. The TBNN is trained to predict the Reynolds stress anisotropic tensor from local invariant inputs and geometry-informed features, including stream function and velocity potential. Its output is processed by a regression model that generates an optimised eddy viscosity field, which is then integrated into the RANS equations as a zero-equation turbulence closure. The framework is evaluated on three turbulent flows over complex geometries: a wavy-bottom channel, a smoothed step and a backward-facing step. Incorporating geometry-informed features significantly enhances model robustness, yielding numerically stable and convergent solutions across all cases. The predicted velocity fields and turbulence distributions closely match large eddy simulation (LES) data, confirming the accuracy of the proposed approach and demonstrating its ability to operate independently of conventional turbulence closures.

Lactotransferrin (LTF), a critical multifunctional glycoprotein, plays an essential role in the immune defence, growth and development, and milk quality of dairy cows. The regulatory mechanisms governing gene expression are intricate, with sequence variations in the promoter region potentially exerting a substantial impact on gene expression. In this study, sequencing analysis of the bovine lactotransferrin promoter region was conducted, leading to the identification of two linked single nucleotide polymorphism (SNP) sites. A significant association between these SNPs and lactotransferrin content was observed in a cohort of 301 Holstein cows. Subsequently, further investigation into the transcriptional activity of various lactotransferrin genotypes was performed by constructing promoter fragments encompassing different lactotransferrin genotypes. The findings reveal that the two SNPs significantly influence the activity of the lactotransferrin promoter, thereby affecting lactotransferrin expression. These results hold substantial implications for advancing our understanding of the regulatory mechanisms underlying lactotransferrin expression and for the genetic enhancement of dairy cows.

Although deep reinforcement learning (DRL) techniques have been extensively studied in the field of robotic manipulators, there is limited research on directly mapping the output of policy functions to the joint space of manipulators. This paper proposes a motion planning scheme for redundant manipulators to avoid obstacles based on DRL, considering the actual shapes of obstacles in the environment. This scheme not only accomplishes the path planning task for the end-effector but also enables autonomous obstacle avoidance while obtaining the joint trajectories of the manipulator. First, a reinforcement learning framework based on the joint space is proposed. This framework uses the joint accelerations of the manipulator to calculate the Cartesian coordinates of the end-effector through forward kinematics, thereby performing end-to-end path planning for the end-effector. Second, the distance between all the linkages of the manipulator and irregular obstacles is calculated in real time based on the Gilbert–Johnson–Keerthi distance algorithm. The reward function containing joint acceleration is constructed with this distance to realize the obstacle avoidance task of the redundant manipulator. Finally, simulations and physical experiments were conducted on a 7-degree-of-freedom manipulator, demonstrating that the proposed scheme can generate efficient and collision-free trajectories in environments with irregular obstacles, effectively avoiding collisions.

Influenced by human activities, microplastics (MPs) are widely distributed in terrestrial ecosystems. However, their ecotoxicity remains unclear. Therefore, we assessed the ecotoxicity of polyamide microplastics (PA-MPs) by investigating their toxic effects on the model insect, the silkworms Bombyx mori (Lepidoptera: Bombycidae). In this study, fifth-instar silkworm larvae were fed mulberry leaves treated with PA-MPs for 120 hours, but no changes in mortality rates were observed. However, the body weight, pupal weight, cocoon weight, egg laying amount, and cocoon shell weight in F0 generation silkworms were significantly reduced. This indicates that PA-MPs have sublethal effects on silkworms. To further investigate the effects of PA-MPs on the offspring of silkworms, we applied the age-stage, two-sex life table analysis. We found that in the PA-MPs treatment group, the duration of the larval and pupal stages of F1 generation silkworms was significantly prolonged, while the lifespan of the adults and total longevity were shortened. Meanwhile, the life history parameters (sxj, exj, lx, fxj, lxmx, and vxj values) and population parameters (R0, λ, r, and T) of F1 generation silkworms in the PA-MPs treatment group were also lower than control. This indicates that PA-MPs have transgenerational effects, affecting the growth, development, and reproduction of F1 generation silkworms. Our research findings demonstrate the sublethal and transgenerational effects of PA-MPs on silkworms, providing evidence for their ecotoxicity.

Prior research on status has focused primarily on the cognitive perspective, exploring the effects of status and offering a limited understanding of the impact of positive status change and its emotional mechanisms. This study draws upon the two-facet model of pride to examine how positive status change influences the behaviors of new status holders. Specifically, we propose that when status differentiation is low, positive status change enhances new status holders' prosocial behavior through their authentic pride, while in cases of high status differentiation, it increases their self-interested behavior through their hubristic pride. To test our hypotheses, we conducted a series of studies, including a laboratory experiment, a scenario experiment, and a time-lagged multilevel and multisource field study. Our multilevel analyses of the data provided strong support for our hypotheses. Our findings shed light on when and why positive status change triggers different behaviors among new status holders, offering important insights into the emotional mechanisms that underlie the effects of status change.

This study investigates the scenario of flow past a circular cylinder in proximity to a moving wall (or equally a body translating in still fluid parallel to a stationary wall). Fifty high-fidelity three-dimensional direct numerical simulations are performed over a parameter space of turbulent Reynolds numbers (Re) of 300 to 1000 combined with gap-to-diameter ratios (G/D) of 0.2 to 3. The flow, hydrodynamic and turbulence characteristics over the (Re, G/D) parameter space are examined in detail. Small-scale rib-like mode B structures and alternate vortex shedding are observed for all cases. The streamwise location for the vortex shedding (quantified by the wake recirculation length Lr) varies strongly with both Re and G/D. The variation of Lr with Re and G/D can be explained by the spanwise circulation $\varGamma_z$ fed into the wake, where the variation trends of Lr and $\varGamma_z$ are inversely correlated. The variations of the mean drag and fluctuating lift coefficients are also governed by the variations in Lr and $\varGamma_z$. The total kinetic energy in the wake region reduces drastically as G/D reduces below 0.8, which is contributed collectively by (i) reduction in the strength of the shed vortices, (ii) downstream movement of the location of vortex shedding and (iii) associated delayed generation of streamwise vortices. The present results on a moving wall also help to explain several flow and hydrodynamic characteristics reported in the literature for a stationary wall, because the moving wall eliminates the complex wall boundary layer and retains a ‘clean’ near-wall effect.

The purposes of this study were: (1) to review the preparation and characterization of the intergrowth between goethite and hematite crystals; and (2) to propose a schematic diagram of the epitaxial relationships among three sets of (100) goethite twin crystals associated with the (001) orientation of the hexagonal prism of hematite. The Fe(ClO4)3 solution was prepared and aged at 70°C, which precipitated goethite initially and produced hematite later with prolonged aging. Goethite and hematite aged for 20 days were observed as star-shaped and hexagonal prisms, respectively. The results suggest that hematite could form later using goethite as a template surface. A selected area electron diffraction (SAED) pattern showed the epitaxial relationship among three sets of (100) goethite intergrowth crystals and hexagonal prisms with the (001) orientation of hematite. Goethite can be produced as lath-, X-, K-, or star-shaped crystals on the (100) orientation, depending on the Fe(ClO4)3 concentrations and the addition of HClO4 to Fe solution samples which were aged for a prolonged period at room temperature. The initial solubility products [(Fe3+)(OH–)3] of the sample solution, rather than the nature of the nuclei, are the key factors governing the formation of goethite or hematite. The addition of acids and high concentrations of iron solutions extend the secondary hydrolysis and induction period (IP) and favor the formation of hematite. The index of the SAED pattern of the star-shaped goethite intergrowth twin crystal has a (100) plane parallel to this basal plane and rotates at a 60° angle between two or three sets of lath-shaped goethite crystals, which share the (011) plane and form goethite twins with ‘interpenetrated’ crystal growth. Stereoscopic viewing using Oak Ridge Thermal Ellipsoid Plot (ORTEP) and CrystalMaker software was deployed to explore the relationship and configuration of oxygen atoms between pseudo-hexagonal (100) goethite associated with hexagonal (001) hematite lattice planes. A schematic diagram of the epitaxial relationship between star-shaped (100) goethite, which is acting as a template facilitating later precipitation of (001) hexagonal prisms of hematite on it, is presented.

Weeds contribute to biodiversity and a wide range of ecosystem functions. It is crucial to map different weed species and analyze their physiological activities. Remote sensing techniques for plant identification, especially hyperspectral imaging, are being developed using spectral response patterns to vegetation for detection and species identification. A library of hyperspectral images of 40 urban weed species in northeast China was established in this study. A terrestrial hyperspectral camera was used to acquire 435 hyperspectral images. The hyperspectral information for each weed species was extracted and analyzed. The spectral characteristics and vegetation indices of different weeds revealed the differences between weed species in the cities of northeast China and indirectly characterized the growth and physiological activity levels of different species, but could not effectively distinguish different species. Five methods—first derivative spectrum (FDS), second derivative spectrum (SDS), standard normal variate (SNV), moving averages (MA), and Savitzky-Golay (SG) smoothing—were used to pretreat the spectral curves to maximize the retention of spectral characteristics while removing the influence of noise. We investigated the application of a convolutional neural network (CNN) with terrestrial hyperspectral remote sensing to identify urban weeds in northeast China. A CNN classification model was established to distinguish weeds from the hyperspectral images and demonstrated a test accuracy of 95.32% to 98.15%. The accuracy of the original spectrum was 97.45%; SNV had the best accuracy (98.15%) and SG was the least accurate (95.32%). This provides a baseline for understanding the hyperspectral characteristics of urban weed species and monitoring their growth. It also contributes to the development of a hyperspectral imaging database with global applicability.

A high-energy, alignment-insensitive, injection-seeded Q-switched Ho:yttrium aluminum garnet (YAG) single-frequency laser is developed. Both the slave Q-switched laser and the seed laser are Ho:YAG ring lasers based on a pair of corner cubic reflectors. The seed laser has an available power of 830 mW at 2096.667 nm. At 100 Hz, the Q-switched Ho:YAG laser provides a single-frequency pulsed output using injection-seeded technology. The 7.3 mJ single-frequency pulse energy from the slave laser has a pulse width of 161.2 ns and is scaled to 33.3 mJ after passing through the Ho:YAG single-pass amplifier. According to the measurement results of the heterodyne beating technique, the single-frequency pulse has a half-width of 4.12 MHz.

Raman spectroscopic analysis was performed on columbite-(Mn) samples from a variety of previously studied rare-element pegmatites in Xinjiang, China, including the Jing'erquan No. 1 spodumene-subtype, Dakalasu No. 1 beryl–columbite-subtype and Kalu'an spodumene-subtype pegmatites, to quantify the relationship between the degree of metamictisation of columbite and Raman spectra. For all of the analysed columbites-(Mn), the position (p) and the full width at half maximum (FWHM) of the strongest band, A1g vibration mode related to the Nb/Ta–O bond, in the Raman spectra have a negative correlation. Combined with previously determined U–Pb isotopic data and major–minor-element data for the columbites-(Mn), the degree of metamictisation was quantified using the alpha-decay dose (D) and displacement per atom (dpa), both of which were corrected for effects caused by annealing. The results demonstrate that the columbite-(Mn) from Jing'erquan and Kalu'an are very crystalline, whereas those from Dakalasu are transitional between crystalline and amorphous stages. The main factor influencing the key parameters, i.e. band position and FWHM, of the strongest Raman band of columbite-(Mn) is metamictisation caused by radiation damage, whereas composition and crystal orientation have limited influence. A set of equations are established to quantify the degree of metamictisation of columbite using the band position and the full width at half maximum: FWHM = 8.309 × ln(aD) + 30.11 (R2 = 0.9861); p = –5.187 × ln(aD) + 867.09 (R2 = 0.966); FWHM = 8.1453 × ln(adpa) + 48.425 (R2 = 0.9822); and p = –5.078 × ln(adpa) + 855.67 (R2 = 0.9594).

Trypanosoma musculi is a, globally distributed, mouse-specific haemoflagellate, of the family Trypanosomatidae, which shares similar characteristics in morphology with Trypanosoma lewisi. The kinetoplast (mitochondrial) DNA of Trypanosomatidae flagellates is comprised of catenated maxicircles and minicircles. However, genetic information on the T. musculi kinetoplast remains largely unknown. In this study, the T. musculi maxicircle genome was completely assembled, with PacBio and Illumina sequencing, and the size was confirmed at 34 606 bp. It consisted of 2 distinct parts: the coding region and the divergent regions (DRs, DRI and II). In comparison with other trypanosome maxicircles (Trypanosoma brucei, Trypanosoma cruzi and T. lewisi), the T. musculi maxicircle has a syntenic distribution of genes and shares 73.9, 78.0 and 92.7% sequence identity, respectively, over the whole coding region. Moreover, novel insertions in MURF2 (630 bp) and in ND5 (1278 bp) were found, respectively, which are homologous to minicircles. These findings support an evolutionary scenario similar to the one proposed for insertions in Trypanosoma cruzi, the pathogen of American trypanosomiasis. These novel insertions, together with a deletion (281 bp) in ND4, question the role of Complex I in T. musculi. A detailed analysis of DRII indicated that it contains numerous repeat motifs and palindromes, the latter of which are highly conservative and contain A5C elements. The comprehensively annotated kinetoplast maxicircle of T. musculi reveals a high degree of similarity between this parasite and the maxicircle of T. lewisi and suggests that the DRII could be a valuable marker for distinguishing these evolutionarily related species.