Omega-3 polyunsaturated fatty acids (PUFAs) docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), possess anti-inflammatory properties, yet their association with obesity-depression comorbidity remains unclear. This study investigated the association among US adults and explored underlying mechanisms. We performed a cross-sectional analysis of 4,423 individuals participating in the National Health and Nutrition Examination Survey (NHANES) 2003–2004 & 2011–2014. Serum fatty acids were quantified by gas chromatography. Obesity was defined using anthropometric criteria, and depression was assessed using the PHQ-9 or antidepressant use. Multivariable logistic regression estimated odds ratios (ORs) per standard deviation (SD) increase in PUFA levels. Mechanistic explore through network pharmacology identified potential pathways, which were examined using correlation analyses with inflammatory indices. Higher omega-3 PUFA levels were associated with lower odds of central obesity comorbid depression in females (OR: 0.82, 95% CI: 0.69–0.96) and older adults (OR: 0.79, 95% CI: 0.64–0.97). DHA was significantly associated with lower odds of central obesity (OR: 0.83, 95% CI: 0.73–0.95), depressive symptoms (OR: 0.88, 95% CI: 0.77–1.00), and their comorbidity (OR: 0.85, 95% CI: 0.74–0.98), whereas no significant associations were found for EPA. Mechanistic exploration implicated DHA in TNF and IL-17 signaling pathways, supported by inverse correlations with monocyte-to-HDL ratio (r: −0.138, P < 0.001) and lymphocyte-to-HDL ratio (r: −0.108, P < 0.001). In conclusion, serum DHA is inversely associated with obesity-depression comorbidity, with potential involvement of anti-inflammatory pathways. These findings underscore the potential of DHA for the management of obesity comorbid depression and the need for further interventional trials.

While 24-hour dietary recalls (24HDRs) are increasingly used to assess polyphenol-disease associations, their performance for measuring total dietary polyphenols and their subclasses remains unknown. In the Anhui Lifestyle Validation Study, 432 community-dwelling adults completed 12-day dietary recalls, structured as 4 seasonal sets of 3 consecutive 24HDRs (2 weekdays and 1 weekend day each) between July 2021 and July 2022. Reproducibility of dietary total polyphenols, flavonoids, lignans and phenolic acids assessed by different number of non-consecutive 24HDRs was evaluated by intraclass correlation coefficient (ICC). Relative validity was evaluated by comparing estimates from different numbers of 24HDRs with the internal reference using deattenuated Spearman correlation coefficients (rc). The reproducibility from 2 24HDRs was weak for these 4 polyphenol categories (ICC: 0.10–0.39), while 3 24HDRs yielded a reasonable reproducibility for total polyphenols (ICC: 0.40, 95% CI: 0.31-0.50), flavonoids (ICC: 0.42, 95% CI: 0.33-0.51), and phenolic acids (ICC: 0.45, 95% CI: 0.16-0.66), but not for lignans (ICC: 0.11, 95% CI: 0.01-0.26). Increasing recall days up to 4–6 seemed not to appreciably improve the reproducibility (ICC range: 0.13-0.17 for lignans, 0.41-0.56 for other polyphenols). The relative validity against the internal reference of these 4 polyphenol categories was moderate for 2 24HDRs (rc: 0.50-0.74) and improved for ≥ 3 24HDRs (rc: 0.76-1.00). Older age, female sex, and weekend administration were associated with lower reproducibility of 3 24HDR-based assessments of phenolic acids or flavonoids. Overall, our results suggest that 3 non-consecutive 24HDRs may have acceptable performance in measuring most dietary polyphenol intake except for lignans.

Little is known about the combined association of physical activity (PA) and dietary quality (DQ) with stroke and its mortality outcomes. This study aims to investigate the individual and combined association of PA and DQ on odds of prevalent stroke and mortality among stroke survivors. We analyzed data from 20,225 adults participating in the 2007–2018 National Health and Nutrition Examination Survey, including 838 stroke survivors. PA was measured by the self-reported metabolic equivalent to task (MET) minutes per week, and DQ by Healthy Eating Index 2020 (HEI-2020). Logistic regression models evaluated associations with the odds of prevalent stroke, and Cox proportional hazards regression models assessed mortality risks among stroke survivors. Compared to no PA - lower DQ (reference), low PA - lower DQ (adjusted OR 0.49, 95%CI 0.32-0.75), low PA - higher DQ (adjusted OR 0.56, 95%CI 0.34-0.92), high PA - lower DQ (adjusted OR 0.66, 95%CI 0.44 - 0.99), and high PA - higher DQ (adjusted OR 0.50, 95%CI 0.34-0.73) were significantly associated with lower odds of stroke. Among stroke survivors, reduced mortality was observed for low PA–higher DQ (adjusted HR 0.43; 95% CI, 0.19–0.95), high PA–lower DQ (HR 0.36; 95% CI, 0.17–0.75), and high PA–higher DQ (HR 0.47; 95% CI, 0.27–0.83). This large observational study showed that a combination of appropriate PA and higher DQ is associated with reduced odds of stroke and mortality among stroke survivors. These findings support lifestyle modification as a strategy for stroke prevention and survivor care.

We develop a three-dimensional numerical scheme for investigating interfacial flows coupled with frictional solid particles. Our approach combines the lattice Boltzmann method (LBM) to model the dynamics of a two-component fluid, and the discrete element method (DEM) to model normal reaction, sliding friction and rolling friction between solid particles and between particles and solid surfaces. Key to the coupling between the fluid and particle dynamics are the momentum exchange method to transfer hydrodynamic forces between the fluids and particles, a geometric boundary condition to tune particle wettability, and a capillary force model describing surface tension forces between particles and liquid–fluid interfaces. We rigorously validate the contact forces by investigating the dynamics of a particle bouncing off a solid surface and rolling down an inclined plane, the hydrodynamic force by the Segrè–Silberberg effect and the capillary force by particle detachment from a liquid–fluid interface. Motivated by the self-cleaning properties of lotus leaves, we apply the method to investigate how drops remove contaminant particles from surfaces. We successfully reproduce scenarios reported experimentally by Naga et al. (2021a Soft Matt. 17(7), 1746–1755) by tuning the particle friction. Furthermore, the LBM–DEM approach allows us to systematically explore the effects of particle friction coefficients, drop size and speed. Our method opens opportunities to study numerous phenomena involving particle dynamics interacting with interfacial flows, including soil erosion, capillary-driven colloidal self-assembly and how raindrops transport microplastics in the environment. It also makes it possible to control parameters that are difficult to tune independently in experiments, including contact angles, surface tension and friction coefficients.

The 4-DOF (four degrees of freedom) parallel manipulator, namely 2PPaRR-2PPaRU, offers three translations and one rotation capabilities, boasting an extensive rotation range, and a regular workspace. Moreover, its workspace can infinitely extend in conjunction with the extension of the driving joints. Nonetheless, the symmetric structure relying on Pa joint design presents performance challenges in the initial configuration and complicates the analytical solution of the forward kinematics, thereby increasing the complexity of dynamics and control. To address these limitations, the structure of the moving platform is modified by coaxially connecting the three joints at the ends of the three limbs to the moving platform. This improvement is followed by analyses of mobility, motion/force transmissibility, and stiffness. The overall reachable workspace area, good transmission workspace ratio, and global stiffness index are then chosen as key objectives for dimensional optimization, thereby achieving satisfactory performance for the new 3T1R PM. Finally, the CAD model with the selected parameters is presented, together with the distributions of motion/force transmission index and virtual stiffness index within the reachable workspace. The results validate the effectiveness of the optimization design.

Dyslipidaemia is associated with chronic low-grade inflammation and immune dysfunction, but the immunological effects of dietary phytosterols in humans remain unclear. We conducted a secondary analysis of an outcome-assessor-blinded, randomised controlled feeding trial to evaluate the effects of a high-phytosterol (HPS) diet, using phytosterol-enriched corn–wheat germ blended oil (CWGO), compared with a low-phytosterol (LPS) diet using peanut oil, on systemic inflammatory markers, humoural immune markers and peripheral blood lymphocyte subsets in Chinese adults with dyslipidaemia. After a 2-week run-in period, 104 participants were randomised to the HPS group (n 52) or the LPS group (n 52) for 12 weeks. In intention-to-treat analyses, the HPS group had a higher CD4+:CD8+ ratio at 12 weeks than the LPS group (adjusted mean difference: 0·561; 95 % CI 0·060, 1·063; P = 0·03) and a lower CD8+ T-cell count (adjusted mean difference: −116·315 cells/μl; 95 % CI −215·781, –16·849; P = 0·02). No significant between-group differences were observed for systemic inflammatory markers, humoral immune markers or most other lymphocyte subset outcomes. In per-protocol analyses, the difference in CD4+:CD8+ ratio remained significant, whereas the reduction in CD8+ T-cell count was attenuated. These exploratory findings suggest that a 12-week phytosterol-enriched CWGO intervention may be associated with changes in T-cell subset balance in adults with dyslipidaemia, although the results should be interpreted cautiously given the exploratory nature of this secondary analysis.

Rapid industrialization and urbanization have led to significant environmental challenges in China. These concerns have created an urgent need for sustainable development through green entrepreneurship among students. The purpose of this study is to determine the direct impact of the entrepreneurial behaviour of the students on green entrepreneurship to promote sustainability and business opportunities. This research also investigated the moderating role of sustainable development goals in students’ entrepreneurial behaviour and green entrepreneurship. The statistical analysis showed that green entrepreneurship is significantly and positively influenced by the entrepreneurial behaviour of students and green entrepreneurship further influences the environmental sustainability and creating business opportunities. The study also confirms that knowledge of sustainable development goals increases the student’s behaviour towards green entrepreneurship. The results of this research are critical for educational institutes to sensitize students’ behaviour towards sustainability and develop in them the potential for business that does not harm the environment. This study contributes significant insights into the correlation between students’ entrepreneurial behaviour, green entrepreneurship, and environmental sustainability. It offers implications for educational institutions to enhance sustainability awareness and foster the growth of eco-friendly businesses among students.

Fluid–structure interaction (FSI) poses a significant computational challenge due to the complex, multiscale nonlinearities of both fluid and structural dynamics. In this study, a novel strongly coupled FSI network is developed for accurate and efficient predictive modelling of FSI problems. Specifically, the framework architecture integrates a physics-constrained convolutional neural network autoencoder (CAE) with a strong coupling (SC) prediction module containing both fluid and structural dynamic prediction modules (DP) that perform recursive prediction simultaneously and interactively. First, the physics-constrained CAE learns low-dimensional nonlinear normal modes (NNMs) representations of the high-dimensional fluid field’s spatiotemporal dynamics. Subsequently, the fluid DP module in the SC module leverages these NNMs combined with structural states determined by embedding the motion equation into the structural DP, to predict the future-state flow fields efficiently. Such a strongly coupled FSI framework is achieved by integrating fluid NNMs and structural states within each time step to recursively correct the learned mapping of the trained CAE and fluid DP modules, thereby efficiently and accurately predicting future-state FSI dynamics simultaneously. The developed SC-CAE-NNM FSI framework is applied to the classic problem of vortex-induced vibrations of a circular cylinder, analysing both laminar and high-$ \textit{Re}$ flows. It is observed that the identified NNMs of fluid flows in association with the structural state achieve superior accuracy in the prediction of the flow fields and structural responses, indicating that the SC scheme effectively captures the dynamic flow characteristics and strong nonlinear interactions. Furthermore, the framework is found to be able to reconstruct small-scale flow structures in high-$ \textit{Re}$ flows accurately and predict structural responses efficiently. Additionally, the analysis of NNMs energy distributions reveals that the majority of the total energy of the flow field is captured by the first four NNMs, demonstrating significant advantages of nonlinear feature representation for efficient reduced-order modelling of complex flows. Overall, this novel framework shows strong capability for accurate and efficient predictive modelling of complex nonlinear dynamics of FSIs.

We prove a strengthened form of a conjecture of Sun on a determinant attached to a binary quadratic form. Let $n>3$ and let $c,d\in \mathbb Z$. If n is composite, then

$$ \begin{align*} \det [(i^2+cij+dj^2)^{n-2}]_{0\leq i,j\leq n-1}\equiv 0 \pmod {n^2} \end{align*} $$

with no condition on c and d. If $n=p$ is prime, the same congruence holds whenever the Legendre symbol $({d}/{p})$ is $-1$. For composite n, a polynomial determinant is divisible by two Vandermonde factors; after specialisation, their product already yields the required square divisor. For prime $n=p$, we estimate the rank of the matrix modulo p. The required rank defect follows from a coefficient cancellation obtained from the involution $t\mapsto d/t$ on $\mathbb F_p^\times $ and the condition $({d}/{p})=-1$.

Currently, the research on the key factors which affect clinical and non-clinical pregnancy in high-quality single blastocyst transfer cycles remains relatively limited. This is particularly true for FET cycles, where the relationship between the transfer of high-quality single blastocysts and pregnancy outcomes has not been fully explored. This study aimed to identify key factors influencing clinical pregnancy outcomes in high-quality single blastocyst frozen-thawed transfer cycles to optimize assisted reproductive technology (ART). Patients under 38 years old who underwent high-quality single blastocyst frozen-thawed embryo transfer were included. Based on clinical pregnancy outcomes, they were divided into clinical pregnancy (Group A) and non-clinical pregnancy (Group B) groups. Key influencing factors were analyzed to guide the selection of blastocysts with the highest pregnancy potential.The result showed that Group B showed significantly higher age and infertility duration, but lower AMH levels, antral follicle count, and endometrial thickness on the day of transfer compared to Group A (P < 0.01). Infertility type also differed significantly (P < 0.01). Blastocyst grading differed between groups (P < 0.01), while E2, LH, P levels, embryo age, and D3 cleavage-stage cell count showed no significant differences (P > 0.05). Multivariate analysis revealed that infertility type, age, infertility duration, and endometrial thickness significantly impacted clinical pregnancy outcomes (P< 0.05), while AMH, antral follicle count, and blastocyst grading had no significant effect. All in all, clinical pregnancy outcomes are significantly influenced by age, infertility type, infertility duration, and endometrial thickness. Early treatment, optimized endometrial conditions, and selecting high-quality blastocysts are recommended to improve pregnancy rates.

This study develops wavenumber–frequency spectrum models for wall-pressure fluctuations in turbulent boundary layers on flat plates and cylinders in compressible flow. Through non-dimensionalisation and solution of the momentum and continuity equations, a unified physical framework integrating near-field pressure and far-field acoustic regions is established, extending Lighthill’s acoustic analogy. Starting from the fluctuating pressure governing equation, Mach number effects in the acoustic region are explicitly introduced for the first time, and unified analytical expressions across the full wavenumber range are derived for both geometries. The proposed models achieve high-precision prediction across the entire wavenumber domain. Validation is performed via cylinder wind tunnel experiments at Mach $0.12$–$0.18$ and flat-plate direct numerical simulation (DNS) at Mach $0.1$–$0.5$. Compared with classical models such as Chase II, Smol’yakov and Corcos, the present model shows better agreement with experimental and DNS data, particularly in low-wavenumber and acoustic regions, improving prediction accuracy by more than $10$ dB. Key findings: (i) acoustic amplitude highly correlates with Mach number, while the convective ridge does not; (ii) the acoustic of flat-plate boundary is defined by $k_{1}^{2} + k_{3}^{2} - (k_{0} - Mak_{1})^{2} = 0$, where $k$ is the wavenumber and $Ma$ is the Mach number; (iii) the cylinder model degenerates to the flat-plate form as the curvature radius approaches infinity, with curvature effects confined mainly to the acoustic region and large circumferential wavenumbers. This work provides a physically self-consistent and practical engineering spectral model with significantly enhanced predictive capability under compressible-flow conditions.