The conventional design method for high-performance concrete (HPC) mixture proportion requires a large amount of trial mixing work to obtain the desired HPC mixture proportion, which consumes a lot of manpower, material resources, and time resources during the trial mixing process. In recent years, an intelligent scheme for HPC mixture proportion design has been developed. To more effectively optimize HPC mixture proportions, this article proposes a novel intelligent HPC mixture proportion design method. Firstly, this article establishes a hybrid multi-objective optimization (MOO) method for HPC mixture proportion design problem, called CNN–NSDBO–EWTOPSIS. In this MOO framework, there are three objective functions, namely the compressive strength (CS) of concrete, cost, and carbon dioxide emissions. Among them, based on the various components of concrete, this article constructs a convolutional neural network (CNN) regression prediction model for predicting the CS of concrete. The calculation of cost and carbon dioxide emissions involves the utilization of two polynomials. Additionally, dung beetle optimizer (DBO) is used to optimize the hyperparameters of the CNN. Furthermore, this article incorporates the constructed CNN regression prediction model and two polynomials as the three objective functions for HPC mixture proportion design problem. This three-objective optimization problem is solved using a non-dominated sorting dung beetle optimizer (NSDBO). Finally, based on the obtained Pareto front, this article obtains a good solution using the entropy weight technique for order preference by similarity to an ideal solution (EWTOPSIS) method. The experimental results indicate that the proposed CNN–NSDBO–EWTOPSIS approach can achieve HPC mixture proportion design.

We report the first shock-tube experiments on Richtmyer–Meshkov instability at a single-mode light–heavy interface accelerated by a strong shock wave with Mach number higher than 3.0. Under the proximity effect of the transmitted shock and its induced secondary compression effect, the interface profile is markedly different from that in weakly compressible flows. For the first time, the validity of the compressible linear theory and the failure of the impulsive model in predicting the linear amplitude evolution in highly compressible flows are verified through experiments. Existing nonlinear and modal models fail to accurately describe the perturbation evolution, as they do not account for the shock proximity and secondary compression effects on interface evolution. The shock proximity effect manifests mainly in the early stages when the transmitted shock remains close to the interface, while the effect of secondary compression manifests primarily at the period when interactions of transverse shocks occur at the bubble tips. Based on these findings, we propose an empirical model capable of predicting the bubble evolution in highly compressible flows.

The multi-robot path planning problem is an NP-hard problem. The coati optimization algorithm (COA) is a novel metaheuristic algorithm and has been successfully applied in many fields. To solve multi-robot path planning optimization problems, we embed two differential evolution (DE) strategies into COA, a self-adaptive differential evolution-based coati optimization algorithm (SDECOA) is proposed. Among these strategies, the proposed algorithm adaptively selects more suitable strategies for different problems, effectively balancing global and local search capabilities. To validate the algorithm’s effectiveness, we tested it on CEC2020 benchmark functions and 48 CEC2020 real-world constrained optimization problems. In the latter’s experiments, the algorithm proposed in this paper achieved the best overall results compared to the top five algorithms that won in the CEC2020 competition. Finally, we applied SDECOA to optimization multi-robot online path planning problem. Facing extreme environments with multiple static and dynamic obstacles of varying sizes, the SDECOA algorithm consistently outperformed some classical and state-of-the-art algorithms. Compared to DE and COA, the proposed algorithm achieved an average improvement of 46% and 50%, respectively. Through extensive experimental testing, it was confirmed that our proposed algorithm is highly competitive. The source code of the algorithm is accessible at: https://ww2.mathworks.cn/matlabcentral/fileexchange/164876-HDECOA.

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.

This study aimed to understand the potassium voltage-gated channel KQT-like subfamily, member 1 gene polymorphism in a rural elderly population in a county in Guangxi and to explore the possible relationship between its gene polymorphism and blood sugar. The 6 SNP loci of blood DNA samples from 4355 individuals were typed using the imLDRTM Multiple SNP Typing Kit from Shanghai Tianhao Biotechnology Co. The data combining epidemiological information (baseline questionnaire and physical examination results) and genotyping results were statistically analyzed using GMDR0.9 software and SPSS22.0 software. A total of 4355 elderly people aged 60 years and above were surveyed in this survey, and the total abnormal rate of glucose metabolism was 16·11 % (699/4355). Among them, male:female ratio was 1:1·48; the age group of 60–69 years old accounted for the highest proportion, with 2337 people, accounting for 53·66 % (2337/4355). The results of multivariate analysis showed that usually not doing farm work (OR 1·26; 95 % CI 1·06, 1·50), TAG ≥ 1·70 mmol/l (OR 1·19; 95 % CI 1·11, 1·27), hyperuricaemia (OR 1·034; 95 % CI 1·01, 1·66) and BMI ≥ 24 kg/m2 (OR 1·06; 95 % CI 1·03, 1·09) may be risk factors for abnormal glucose metabolism. Among all participants, rs151290 locus AA genotype, A allele carriers (AA+AC) were 0.70 times more likely (0.54 to 0.91) and 0.82 times more likely (0.70 to 0.97) to develop abnormal glucose metabolism than CC genotype carriers, respectively. Carriers of the T allele at the rs2237892 locus (CT+TT) were 0.85 times more likely to have abnormal glucose metabolism than carriers of the CC genotype (0.72 to 0.99); rs2237897 locus CT gene. The possibility of abnormal glucose metabolism in the carriers of CC genotype, TT genotype and T allele (CT + TT) is 0·79 times (0·67–0·94), 0·74 times (0·55–0·99) and 0·78 times (0·66, 0·92). The results of multifactor dimensionality reduction showed that the optimal interaction model was a three-factor model consisting of farm work, TAG and rs2237897. The best model dendrogram found that the interaction between TAG and rs2237897 had the strongest effect on fasting blood glucose in the elderly in rural areas, and they were mutually antagonistic. Environment–gene interaction is an important factor affecting abnormal glucose metabolism in the elderly of a county in Hechi City, Guangxi.

Regolith-hosted rare earth element (REE) deposits hosted by the granitic regolith in South China provide >90% of the world’s heavy REEs. Kaolinite is one of the major carriers of REE ions in regolith. The formation and transformation of kaolinite can be affected by chemical weathering and hydrodynamic conditions, but the contribution of each factor has not been evaluated. This study systematically investigated the variation in abundance of phyllosilicate minerals and structural order of kaolinite in the Renju regolith-hosted REE deposit. The total abundance of 1:1 phyllosilicate minerals increased upwards along the profile from Section I to Section III. However, semi-quantitative analyses indicated that Section III-1 (depth at 10–16 m) featured an evident decrease in both abundance and structural order of kaolinite upward along the profile. The morphological feature and abundance of kaolinite revealed intensive kaolinite-to-halloysite transformation and kaolinite dissolution in Section III-1. This suggests that the alternating wetting and drying zone in Section III-1 provided a favorable kinetic environment for the entry of water molecules into the kaolinite interlayer and the kaolinite-to-halloysite transformation, resulting in both lower structural order and abundance of kaolinite in Section III-1. Moreover, REE ions started to be enriched from the alternating wetting and drying zone and formed high-grade ores at the lower part of the water table, due to a significant increase in pore water and decrease in the seepage velocity. Therefore, the abundance and structural order of secondary kaolinite can serve as important indicators of hydrodynamic changes in regolith, as well as the mineralization of regolith-hosted REEs.

In preparation for an experiment with a laser-generated intense proton beam at the Laser Fusion Research Center at Mianyang to investigate the 11B(p,α)2α reaction, we performed a measurement at very low proton energy between 140 keV and 172 keV using the high-voltage platform at the Institute of Modern Physics, Lanzhou. The aim of the experiment was to test the ability to use CR-39 track detectors for cross-section measurements and to remeasure the cross-section of this reaction close to the first resonance using the thick target approach. We obtained the cross-section σ = 45.6 ± 12.5 mb near 156 keV. Our result confirms the feasibility of CR-39 type track detector for nuclear reaction measurement also in low-energy regions.

Organic, ionic soil stabilizers (OISS) are designed to regulate directly the hydration properties of clay minerals to improve their engineering behavior. The steps involved in this regulation by OISS are unclear and this might limit their application in the current construction environment in China. The purpose of the present study was to reveal the origin of changes in hydration properties of four typical clay samples (with clay mineral contents of >90 wt.%: Na-bentonite, Ca-bentonite, illite, and kaolinite) as affected by OISS. The water-retention capacity of each clay was measured first through liquid limit and water-vapor adsorption tests. Then, the changes in hydration sites, such as exchangeable cations and the surfaces of minerals, were investigated by a series of microscopic measuring and testing techniques. Finally, infrared spectroscopy (IR) and thermal analysis were performed to verify the regulation of hydration properties by OISS. The results suggested that the exchangeable cation and surface changes controlled the regulation of hydration properties. OISS could cause some of the exchangeable cations to become free ions and disrupt the interaction between some cations and water molecules by its long organic chains; thus, the amount of hydrated cations decreased. In addition, the long organic chains covered the mineral surface and weakened its adsorption capacity. Furthermore, the long chains had cementitious qualities, connecting them to the crystalline layer and resulting in more aggregated clay particles and a smaller specific surface area (SSA). With the decrease in the number of cations and in the SSA by OISS, the hydration of the four clay samples decreased, especially in the case of bentonite.

High-intensity vortex beams with tunable topological charges and low coherence are highly demanded in applications such as inertial confinement fusion (ICF) and optical communication. However, traditional optical vortices featuring nonuniform intensity distributions are dramatically restricted in application scenarios that require a high-intensity vortex beam owing to their ineffective amplification resulting from the intensity-dependent nonlinear effect. Here, a low-coherence perfect vortex beam (PVB) with a topological charge as high as 140 is realized based on the super-pixel wavefront-shaping technique. More importantly, a globally adaptive feedback algorithm (GAFA) is proposed to efficiently suppress the original intensity fluctuation and achieve a flat-top PVB with dramatically reduced beam speckle contrast. The GAFA-based flat-top PVB generation method can pave the way for high-intensity vortex beam generation, which is crucial for potential applications in ICF, laser processing, optical communication and optical trapping.

Trace elements may play an important role in obesity. This study aimed to assess the plasma and dietary intake levels of four trace elements, Mn, Cu, Zn and Se in a rural Chinese population, and analyse the relationship between trace elements and obesity. A cross-sectional study involving 2587 participants was conducted. Logistic regression models were used to analyse the association between trace elements and obesity; restricted cubic spline (RCS) models were used to assess the dose–response relationship between trace elements and obesity; the weighted quantile sum (WQS) model was used to examine the potential interaction of four plasma trace elements on obesity. Logistic regression analysis showed that plasma Se concentrations in the fourth quartile (Q4) exhibited a lower risk of developing obesity than the first quartile (Q1) (central obesity: OR = 0·634, P = 0·002; general obesity: OR = 0·525, P = 0·005). Plasma Zn concentration in the third quartile (Q3) showed a lower risk of developing obesity in general obesity compared with the first quartile (Q1) (OR = 0·625, P = 0·036). In general obesity, the risk of morbidity was 1·727 and 1·923 times higher for the second and third (Q2, Q3) quartiles of dietary Mn intake than for Q1, respectively. RCS indicated an inverse U-shaped correlation between plasma Se and obesity. WQS revealed the combined effects of four trace elements were negatively associated with central obesity. Plasma Zn and Se were negatively associated with obesity, and dietary Mn was positively associated with obesity. The combined action of the four plasma trace elements had a negative effect on obesity.