The Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) resulted in many ice-sheet simulations from multiple ice-sheet models. To date, no model weighting studies have analyzed or quantified the model performance, possible duplication of the ISMIP6 ice-sheet models and the effect on mass loss projections. In this study, we adopt a model weighting scheme for the ISMIP6-Greenland that accounts for both model performance compared to observation and model similarity due to possible duplication. We choose ice velocity and thickness for the measurement of model performance, and we use all suitable variables to compute similarity indexes. We update the sea level rise contribution from ISMIP6-Greenland by the end of this century with the weights, and we find that, although the multi-model mean is not considerably shifted (mostly within $ \pm 1{\text{cm}}$), the model spreads are reduced by 10–30% after applying the model weights. The magnitude of reduction varies largely among experiments and types of model weights applied. In general, we find that the model weighting scheme is skillful in producing model weights that effectively and reasonably quantify the model performance and inter-dependency, which can potentially benefit the future phase of the Ice Sheet Model Intercomparison Project, i.e. ISMIP7.

Research on the association between the Chinese visceral adiposity index (CVAI) and hyperuricaemia (HUA) is scarce, and whether the association differs by sex is unclear. This research aimed to explore sex-specific associations between CVAI and HUA and to compare CVAI’s predictive performance with other adiposity indices using data from 22 171 adults (30–79 years) in the China Multi-Ethnic Cohort study (Chongqing region). The prevalence of HUA was 20·9 % in men and 9·7 % in women. Multivariable logistic regression analyses were utilised to assess the adjusted OR and 95 % CI. After multivariable adjustment, CVAI was associated with HUA in men (OR Q4 v. Q1 = 3·31, 95 % CI 2·73, 4·03) and women (OR Q4 v. Q1 = 7·20, 95 % CI 5·12, 10·12). Moreover, significant interactions were observed between BMI and CVAI on HUA in both sexes (all Pinteraction < 0·001), with the strongest associations in those with BMI < 24·0 kg/m2. The OR (95 % CI) across different BMI groups (< 24·0, 24·0–27·9, ≥ 28·0 kg/m²) were 1·87 (1·63, 2·13), 1·65 (1·48, 1·85) and 1·30 (1·14, 1·49) for men and 2·76 (2·18, 3·51), 2·46 (1·98, 3·07) and 1·87 (1·47, 2·39) for women, respectively. Additionally, CVAI showed satisfactory predictive performance for HUA in women, with the largest area under the receiver operating characteristic curve of 0·735, but not in men (0·660). These findings suggest a close association between CVAI and HUA, particularly pronounced in those with BMI < 24·0 kg/m², and a stronger association in women than in men.

This study examined the relationship between total body fat percentage (TBFP), trunk fat percentage (TFP), and urinary flow rate (UFR) using NHANES data (2011–2018) from 10 521 participants aged 18–59. Multivariable-adjusted regression models assessed associations between dual-energy X-ray absorptiometry-measured fat percentages and UFR. Results showed that increased TBFP and TFP were inversely associated with UFR (TBFP: β = −0·013, 95 % CI [–0·018, −0·007]; TFP: β = –0·014, 95 % CI [–0·018, −0·009]). Stratified analyses revealed gender differences: in males, higher TBFP and TFP correlated with lower UFR (TBFP: β = –0·011, 95 % CI [−0·019, −0·004]; TFP: β = –0·016, 95 % CI [−0·022, −0·009]), but this association was absent in males aged 18–35. In females, both TBFP and TFP were consistently linked to reduced UFR across all age groups (TBFP: β = −0·016, 95 % CI [−0·023, −0·008]; TFP: β = −0·012, 95 % CI [−0·019, −0·006]). These findings suggest that body and trunk fat accumulation negatively impact UFR, with stronger effects in females and age-dependent variations in males. Further research should explore mechanisms behind these disparities to guide targeted interventions.

In this study, direct numerical simulation of the particle dispersion and turbulence modulation in a sonic transverse jet injected into a supersonic cross-flow with a Mach number of 2 was carried out with the Eulerian–Lagrangian point-particle method. One single-phase case and two particle-laden cases with different particle diameters were simulated. The jet and particle trajectories, the dispersion characteristics of particles, and the modulation effect of particles on the flow were investigated systematically. It was found that large particles primarily accumulate around shear layer structures situated on the windward side of the jet trajectory. In contrast, small particles exhibit radial transport, accessing both upstream and downstream recirculation zones. Moreover, small particles disperse extensively within the boundary layer and large-scale shear layers, evidently influenced by the streamwise vortices. The particles increase the mean wall-normal velocity near the wall in the wake region of the transverse jet, while reducing the mean streamwise and wall-normal velocities in outer regions. Particles significantly alter the flow velocity adjacent to shock fronts. In particular, the turbulent fluctuations near the windward barrel shock and bow shock are reduced, while those around the leeward barrel shock are increased. An upward displacement of the bow shock in the wall-normal direction is also observed due to particles. In the regions away from the shocks, small particles tend to amplify the Reynolds stress, while large particles attenuate the turbulent kinetic energy.

The associations between obesity and liver diseases are complex and diverse. To explore the causal relationships between obesity and liver diseases, we applied two-sample Mendelian randomisation (MR) and multivariable MR analysis. The data of exposures (BMI and WHRadjBMI) and outcomes (liver diseases and liver function biomarker) were obtained from the open genome-wide association study database. A two-sample MR study revealed that the genetically predicted BMI and WHRadjBMI were associated with non-alcoholic fatty liver disease, liver fibrosis and autoimmune hepatitis. Obesity was not associated with primary biliary cholangitis, liver failure, liver cell carcinoma, viral hepatitis and secondary malignant neoplasm of liver. A higher WHRadjBMI was associated with higher levels of biomarkers of lipid accumulation and metabolic disorders. These findings indicated independent causal roles of obesity in non-alcoholic fatty liver disease, liver fibrosis and impaired liver metabolic function rather than in viral or autoimmune liver disease.

A comprehensive direct numerical simulation of electroconvection (EC) turbulence caused by strong unipolar charge injection in a two-dimensional cavity is performed. The EC turbulence has strong fluctuations and intermittency in the closed cavity. Several dominant large-scale structures are found, including two vertical main rolls and a single primary roll. The flow mode significantly influences the charge transport efficiency. A nearly $Ne \sim T^{1/2}$ scaling stage is observed, and the optimal $Ne$ increment is related to the mode with two vertical rolls, while the single roll mode decreases the charge transport efficiency. As the flow strength increases, EC turbulence transitions from an electric force-dominated mode to an inertia-dominated mode. The former utilizes the Coulomb force more effectively and allocates more energy to convection. The vertical mean profiles of charge, electric field and energy budget provide intuitive information on the spatial energy distribution. With the aid of the energy-box technique, a detailed energy transport evolution is illustrated with changing electric Rayleigh numbers. This exploration of EC turbulence can help explain more complicated electrokinetic turbulence mechanisms and the successful utilization of Fourier mode decomposition and energy-box techniques is expected to benefit future EC studies.

The aim of this study is to evaluate the infection risk of aircraft passengers seated within and beyond two rows of the index case(s) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A(H1N1)pdm09 virus, and SARS-CoV-1. PubMed databases were searched for articles containing information on air travel–related transmission of SARS-CoV-2, influenza A(H1N1)pdm09 virus, and SARS-CoV-1 infections. We performed a meta-analysis of inflight infection data. In the eight flights where the attack rate could be calculated, the inflight SARS-CoV-2 attack rates ranged from 2.6% to 16.1%. The risk ratios of infection for passengers seated within and outside the two rows of the index cases were 5.64 (95% confidence interval (CI):1.94–16.40) in SARS-CoV-2 outbreaks, 4.26 (95% CI:1.08–16.81) in the influenza A(H1N1)pdm09 virus outbreaks, and 1.91 (95% CI:0.80–4.55) in SARS-CoV-1 outbreaks. Furthermore, we found no significant difference between the attack rates of SARS-CoV-2 in flights where the passengers were wearing masks and those where they were not (p = 0.22). The spatial distribution of inflight SARS-CoV-2 outbreaks was more similar to that of the influenza A(H1N1)pdm09 virus outbreaks than to that of SARS-CoV-1. Given the high proportion of asymptomatic or pre-symptomatic infection in SARS-CoV-2 transmission, we hypothesised that the proximity transmission, especially short-range airborne route, might play an important role in the inflight SARS-CoV-2 transmission.

The timely identification of the high-risk groups for nosocomial infections (NIs) plays a vital role in its prevention and control. Therefore, it is crucial to investigate whether the ABO blood group is a risk factor for NI. In this study, patients with NI and non-infectionwere matched by the propensity score matching method and a logistic regression model was used to analyse the matched datasets. The study found that patients with the B&AB blood group were susceptible to Escherichia coli (OR = 1.783, p = 0.039); the A blood group were susceptible to Staphylococcus aureus (OR = 2.539, p = 0.019) and Pseudomonas aeruginosa (OR = 5.724, p = 0.003); the A&AB blood group were susceptible to Pseudomonas aeruginosa (OR = 4.061, p = 0.008); the AB blood group were vulnerable to urinary tract infection (OR = 13.672, p = 0.019); the B blood group were susceptible to skin and soft tissue infection (OR = 2.418, p = 0.016); and the B&AB blood group were vulnerable to deep incision infection (OR = 4.243, p = 0.043). Summarily, the patient’s blood group is vital for identifying high-risk groups for NIs and developing targeted prevention and control measures for NIs.

In this work, we propose using an ensemble Kalman method to learn a nonlinear eddy viscosity model, represented as a tensor basis neural network, from velocity data. Data-driven turbulence models have emerged as a promising alternative to traditional models for providing closure mapping from the mean velocities to Reynolds stresses. Most data-driven models in this category need full-field Reynolds stress data for training, which not only places stringent demand on the data generation but also makes the trained model ill-conditioned and lacks robustness. This difficulty can be alleviated by incorporating the Reynolds-averaged Navier–Stokes (RANS) solver in the training process. However, this would necessitate developing adjoint solvers of the RANS model, which requires extra effort in code development and maintenance. Given this difficulty, we present an ensemble Kalman method with an adaptive step size to train a neural-network-based turbulence model by using indirect observation data. To our knowledge, this is the first such attempt in turbulence modelling. The ensemble method is first verified on the flow in a square duct, where it correctly learns the underlying turbulence models from velocity data. Then the generalizability of the learned model is evaluated on a family of separated flows over periodic hills. It is demonstrated that the turbulence model learned in one flow can predict flows in similar configurations with varying slopes.

In this paper, we study the existence and concentration behaviour of multi-peak standing waves for a singularly perturbed Davey–Stewartson system, which arises in the theory of shallow water waves. For this purpose, we first give a sharp threshold of the existence of ground-state solutions to the related limiting problem. Next, combining the penalization method and the regularity theory of elliptic equations, we construct a family of positive solutions concentrating around any prescribed finite set of local minima, possibly degenerate, of the potential. A feature of this analysis is that we do not need any uniqueness or non-degeneracy conditions for the limiting equation. To the best of our knowledge, this paper is the first study dealing with the study of concentrating solutions for Davey–Stewartson systems. We emphasize that with respect to the classical Schrödinger equation, the presence of a singular integral operator in the Davey–Stewartson system forces the implementation of new ideas to obtain the existence of multi-peak solutions.

The study was conducted to determine the effects of three dietary Se sources, such as sodium-selenite (S-S), seleno-yeast (S-Y) and seleno-methionine (S-M), on Se concentration, glutathione peroxidase (GPX) and TXNRD activities, and mRNA expression of fifteen representative selenoproteins, and protein expression of four endoplasmic reticulum-resided selenoproteins in a wide range of tissues of yellow catfish. Compared with S-S and S-M groups, dietary S-Y significantly decreased growth performance and feed utilisation of yellow catfish. Dietary Se sources significantly influenced Se contents in the spleen, dorsal muscle and the kidney, GPX activities in spleen, kidney, intestine, muscle and mesenteric fat, and TXNRD activities in the heart, intestine and mesenteric fat. Among ten tested tissues, dietary Se sources influenced mRNA expression of GPX4 and SELENOK in three tissues; GPX3, SELENOS and TXNRD2 in four tissues; SELENOF, SELENON and DIO2 in five tissues; SELENOM, GPX1/2 and TXNRD3 in six tissues; SELENOW in seven tissue and SELENOP and SELENOT in eight tissues. Based on these observations above, S-S and S-M seem to be suitable Se sources for improving growth performance and feed utilisation of yellow catfish. Dietary Se sources differentially influence the expression of selenoproteins in various tissues of yellow catfish. For the first time, we determined the expression of selenoproteins in fish in responses to dietary Se sources, which contributes to a better understanding of the functions and regulatory mechanisms of selenoporteins.

Shaded coffee systems can mitigate climate change by fixation of atmospheric carbon dioxide (CO2) in soil. Understanding soil organic carbon (SOC) storage and the factors influencing SOC in coffee plantations are necessary for the development of sound land management practices to prevent land degradation and minimize SOC losses. This study was conducted in the main coffee-growing regions of Yunnan; SOC concentrations and storage of shaded and unshaded coffee systems were assessed in the top 40 cm of soil. Relationships between SOC concentration and factors affecting SOC were analysed using multiple linear regression based on the forward and backward stepwise regression method. Factors analysed were soil bulk density (ρb), soil pH, total nitrogen of soil (N), mean annual temperature (MAT), mean annual moisture (MAM), mean annual precipitation (MAP) and elevations (E). Akaike's information criterion (AIC), coefficient of determination (R2), root mean square error (RMSE) and residual sum of squares (RSS) were used to describe the accuracy of multiple linear regression models. Results showed that mean SOC concentration and storage decreased significantly with depth under unshaded coffee systems. Mean SOC concentration and storage were higher in shaded than unshaded coffee systems at 20–40 cm depth. The correlations between SOC concentration and ρb, pH and N were significant. Evidence from the multiple linear regression model showed that soil bulk density (ρb), soil pH, total nitrogen of soil (N) and climatic variables had the greatest impact on soil carbon storage in the coffee system.

Sugarcane brown rust, caused by Puccinia melanocephala, is one of the main diseases of sugarcane in China. The identification and discovery of new resistance genes have important theoretical and practical significance for preventing outbreaks of brown rust and ensuring the sustainable production of sugarcane. To screen for polymorphic simple-sequence repeat (SSR) molecular markers for localization of brown rust resistance genes, we used two populations that are suitable for genetic linkage map construction and mapping of new resistance genes to construct resistant and susceptible genetic pools. We then screened 449 pairs of primers to identify polymorphic SSR markers in the parental lines and the resistant/susceptible genetic pools. The results showed that 25 pairs of primers directed amplification of polymorphic DNA fragments between the parents of the cross combination ‘Yuetang 03-393’ × ‘ROC 24’, and 16 pairs of primers amplified polymorphic fragments between the parents of the cross combination ‘Liucheng 03-1137’ × ‘Dezhe 93-88’. Four pairs of primers (SMC236CG, SCESSR0928, SCESSR0636 and SCESSR2551) amplified polymorphic DNA fragments between the parental lines and the resistant/susceptible genetic pools in ‘Yuetang 03-393’ × ‘ROC 24’. The results of this study will establish a solid foundation for the mapping of new brown rust resistance genes, genetic linkage map construction and the development of closely-associated molecular markers in sugarcane.