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.

Butachlor is a herbicide extensively employed in rice (Oryza sativa L.) cultivation but historically under-investigated for its toxicological impacts on terrestrial vegetation. This study examines the dose-dependent effects of butachlor on the germination and antioxidant defense mechanisms in the seeds of Asian tape grass [Vallisneria natans (Lour.) H. Hara], an important submerged plant species widely distributed in the agricultural ponds. In a hydroponic setup, seeds were exposed to four concentrations of butachlor (0, 20, 200, and 2,000 μg ai L−1), and cultivated under controlled light conditions to quantify germination rates and assess oxidative stress responses. Our findings showed that butachlor concentrations up to 20 μg L−1 had no effect on the germination rate of V. natans seeds, while germination rates decreased by 6.0% and 8.7% at 200 and 2,000 μg L−1, respectively. At 2,000 μg L−1, malondialdehyde (MDA) content increased by 5.7 nmol g−1 FW, and catalase (CAT) activity declined by 21%, indicating oxidative damage. Additionally, the antioxidants proline (Pro) and glutathione (GSH) were upregulated under 20 μg L−1 butachlor treatment after 12 h, contributing to reactive oxygen species (ROS) scavenging and cellular stability. This study highlights the nuanced interactions between butachlor exposure and the antioxidant defenses in V. natans, providing valuable insights into the ecological impacts of herbicide pollution. Understanding these interactions is crucial for development of sustainable agricultural practices and management of herbicide resistance in aquatic systems.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.

Overnutrition during before and pregnancy can cause maternal obesity and raise the risk of maternal metabolic diseases during pregnancy, and in offspring. Lentinus edodes may prevent or reduce obesity. This study aimed to to assess Lentinus edodes fermented products effects on insulin sensitivity, glucose and lipid metabolism in maternal and offspring, and explore its action mechanism. A model of overnutrition during pregnancy and lactation was developed using a 60 % kcal high-fat diet in C57BL6/J female mice. Fermented Lentinus edodes (FLE) was added to the diet at concentrations of 1 %, 3 %, and 5 %. The results demonstrated that FLE to the gestation diet significantly reduced serum insulin levels and homeostatic model assessment for insulin resistance (HOMA-IR) in pregnant mice. FLE can regulate maternal lipid metabolism and reduce fat deposition. Meanwhile, the hepatic phosphoinositide-3-kinase-protein kinase (PI3K/AKT) signaling pathway was significantly activated in the maternal mice. There is a significant negative correlation between maternal FLE supplementation doses and offspring body fat percentage and visceral fat content. Furthermore, FLE supplementation significantly increased offspring weaning litter weight, significantly reduced fasting glucose level, serum insulin level, HOMA-IR and serum glucose level, significantly activated liver PI3K/AKT signaling pathway in offspring, and upregulated the expression of liver lipolytic genes adipose triglyceride lipase, hormone-sensitive lipase and carnitine palmitoyltransferase 1 mRNA. Overall, FLE supplementation can regulate maternal lipid metabolism and reduce fat deposition during pregnancy and lactation, and it may improve insulin sensitivity in pregnant mothers and offspring at weaning through activation of the PI3K/AKT signaling pathway.

A dual-beam platform is developed for all-optical Thomson/Compton scattering, with versatile parameter tuning capabilities including electron energy, radiation energy, radiation polarization, etc. By integrating this platform with a 200 TW Ti:sapphire laser system, we demonstrate the generation of inverse Compton scattering X-/gamma-rays with tunable energies ranging from tens of keV to MeV. The polarization of X-/gamma-rays is manipulated by adjusting the polarization of the scattering laser. In the near future, by combining this platform with multi-PW laser facilities, our goal is to explore the transition from nonlinear Thomson scattering to nonlinear Compton scattering, ultimately verifying theories related to strong-field quantum electrodynamics effects induced by extreme scattering.

Under the coupling effect of node position deviation, joint clearance and wear factors, the complex landing gear retraction mechanism suffers from low kinematic accuracy, slow retraction performance and shortened reliable life. Addressing these issues, a time-dependent reliability analysis and optimisation design method for the kinematic accuracy of the retraction mechanism is proposed, considering the uncertainty of node position deviation, initial clearance, and dynamic multi-joint wear. Initially, a wear prediction model and a dynamic model of the retraction mechanism considering node position deviation and joint clearance are established to analyse their influence on retraction accuracy and joint wear depth. Subsequent retraction testing under various working conditions is conducted to ascertain the critical failure condition and validate the simulation model. The time-dependent kinematic accuracy reliability model, accounting for the dynamic evolution of wear clearance, is then established to assess reliability variation with retraction cycles. Finally, the reliability optimisation design focusing on hole-axis matching accuracy aims to strike a balance between accuracy cost and reliability, thereby enhancing performance and prolonging operational life.

Taihe silk chicken (Gallus gallus domesticus Brisson) are prized for their nutritional value but face challenges like low productivity and feed efficiency. Broussonetia papyrifera (BP), rich in nutrients, is mainly used in ruminant feed. This study investigates the effects of fermented BP (FBP) on the laying performance, egg quality, and gut microbiota of Taihe silk chicken during peak laying period. A total of 240 chickens were randomly assigned to four treatments (five replicates/treatments) with a basal diet (CON), a basal diet + 2% FBP (T2), a basal diet + 4% FBP (T4), and a basal diet + 8% FBP (T8) for 75 d. Results showed that the average daily feed intake and yolk color in the 8% FBP group were significantly increased by 12.21% and 11.78%, respectively (P < 0.05). Yolk folate content of the 4% and 8% FBP groups was significantly increased by 32.73% and 59.76%, respectively (P < 0.05). Zinc content in the yolk of the 8% FBP group was significantly increased by 14.22% (P< 0.05). The FBP group influenced the fatty acid composition of the yolk, and 8% FBP significantly decreased the n-6 unsaturated fatty acid (PUFA) to n-3 PUFA ratio (P< 0.05). FBP also increased the ratio of villus height, and crypt depth significantly increased in the duodenum, jejunum and ileum (P< 0.05). The 16S rRNA sequencing revealed that FBP altered cecal microbiota, increasing the relative abundance of Bacteroides, Rikenellaceae_RC9_gut_group, and Alistipes, while reducing the relative abundance of Olsenella and Ruminococcaceae UCG-005. Correlation analysis suggests that the FBP may enhance the growth performance and egg composition by modulating gut microbiota. In conclusion, this study confirms that adding FBP to the diet improves egg quality, composition, intestinal structure, and gut microbiota in Taihe silk chicken. These insights are valuable for optimizing FBP utilization in Taihe silk chicken production.

Bovine mastitis harms milk quality and cattle health. Val-Pro-Pro (VPP) and Ile-Pro-Pro (IPP) are well-known milk-derived bioactive peptides with anti-inflammatory activity. However, the impact of VPP and IPP on mastitis remain unknown. This study aimed to investigate the anti-inflammatory effects and the underlying mechanisms of VPP and IPP in lipopolysaccharide (LPS)-induced inflammation. When cells were treated with LPS (1 µg/mL) for 24 h, the protein levels of pro-inflammatory factors (tumor necrosis factor-α (TNF-α), interleukin(IL)-1β and IL-6)) and chemokine (monocyte chemotactic protein-1 (MCP-1)) were markedly increased, and the protein level of anti-inflammatory cytokine (IL-10) was reduced. Both VPP and IPP with concentrations of 50 and 100 µM reversed these phenomena and further inhibited the protein expression of β-casein induced by LPS. In a mouse mastitis model, different concentrations of VPP and IPP (300, 600 µM/kg) pretreatment alleviated histopathological lesions in the mammary gland and suppressed the mRNA expression of TNFα, IL1β, and IL6 induced by LPS. VPP and IPP also maintained the integrity of the blood–milk barrier in mice. RNA-seq analyses indicated that enriched phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase (MAPK) signaling pathways likely contribute to the changes observed (P < 0.05 and |log2 fold change (FC)| ≥ 1). Notably, fibronectin was identified as an important hub by protein–protein interaction (PPI) analysis and molecular docking combined with molecular dynamics simulation. In summary, VPP and IPP exerted a protective effect on LPS-induced inflammation by regulating PI3K/AKT signaling pathway via fibronectin.

Little is known about the association between iodine nutrition status and bone health. The present study aimed to explore the connection between iodine nutrition status, bone metabolism parameters, and bone disease (osteopenia and osteoporosis). A cross-sectional survey was conducted involving 391, 395, and 421 adults from iodine fortification areas (IFA), iodine adequate areas (IAA), and iodine excess areas (IEA) of China. Iodine nutrition status, bone metabolism parameters and BMD were measured. Our results showed that, in IEA, the urine iodine concentrations (UIC) and serum iodine concentrations (SIC) were significantly higher than in IAA. BMD and Ca2+ levels were significantly different under different iodine nutrition levels and the BMD were negatively correlated with UIC and SIC. Univariate linear regression showed that gender, age, BMI, menopausal status, smoking status, alcohol consumption, UIC, SIC, free thyroxine, TSH, and alkaline phosphatase were associated with BMD. The prevalence of osteopenia was significantly increased in IEA, UIC ≥ 300 µg/l and SIC > 90 µg/l groups. UIC ≥ 300 µg/l and SIC > 90 µg/l were risk factors for BMD T value < –1·0 sd. In conclusion, excess iodine can not only lead to changes in bone metabolism parameters and BMD, but is also a risk factor for osteopenia and osteoporosis.

This paper provides an overview of the current status of ultrafast and ultra-intense lasers with peak powers exceeding 100 TW and examines the research activities in high-energy-density physics within China. Currently, 10 high-intensity lasers with powers over 100 TW are operational, and about 10 additional lasers are being constructed at various institutes and universities. These facilities operate either independently or are combined with one another, thereby offering substantial support for both Chinese and international research and development efforts in high-energy-density physics.

Skin-friction drag reduction (DR) in a turbulent boundary layer (TBL) using plasma-generated streamwise vortices (PGSVs) is governed by plasma-induced spanwise wall-jet velocity $W$, the distance $L$ between the positive electrodes of two adjacent plasma actuators (PAs) and the friction Reynolds number $Re_\tau$. It is found experimentally that DR increases logarithmically with the growing maximum spanwise mean velocity $\overline {W}_{max}^+$ but decreases with rising $L^+$ and $Re_\tau$, where superscript ‘+’ denotes normalization by the inner scales. It is further found from theoretical and empirical scaling analyses that the dimensionless drag variation $\Delta F = g_1 (\overline {W}_{max}^+, L^+, {Re_\tau })$ may be reduced to $\Delta F = g_2 (\xi )$, where $g_1$ and $g_2$ are different functions and the scaling factor $\xi = [k_{2} \log _{10} (k_{1} \overline {W}_{max }^{+} ) ] / (L^{+} Re_{\tau } )$ ($k_{2}$ and $k_{1}$ are constants) is physically the circulation of the PGSVs. Discussion is conducted based on $\Delta F = g_2 (\xi )$, which provides important insight into the physics of TBL control based on PAs.

The betatron radiation source features a micrometer-scale source size, a femtosecond-scale pulse duration, milliradian-level divergence angles and a broad spectrum exceeding tens of keV. It is conducive to the high-contrast imaging of minute structures and for investigating interdisciplinary ultrafast processes. In this study, we present a betatron X-ray source derived from a high-charge, high-energy electron beam through a laser wakefield accelerator driven by the 1 PW/0.1 Hz laser system at the Shanghai Superintense Ultrafast Laser Facility (SULF). The critical energy of the betatron X-ray source is 22 ± 5 keV. The maximum X-ray flux reaches up to 4 × 109 photons for each shot in the spectral range of 5–30 keV. Correspondingly, the experiment demonstrates a peak brightness of 1.0 × 1023 photons·s−1·mm−2·mrad−2·0.1%BW−1, comparable to those demonstrated by third-generation synchrotron light sources. In addition, the imaging capability of the betatron X-ray source is validated. This study lays the foundation for future imaging applications.

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.

The ubiquitous marine radiocarbon reservoir effect (MRE) constrains the construction of reliable chronologies for marine sediments and the further comparison of paleoclimate records. Different reference values were suggested from various archives. However, it remains unclear how climate and MREs interact. Here we studied two pre-bomb corals from the Hainan Island and Xisha Island in the northern South China Sea (SCS), to examine the relationship between MRE and regional climate change. We find that the MRE from east of Hainan Island is mainly modulated by the Southern Asian Summer Monsoon-induced precipitation (with 11.4% contributed to seawater), rather than wind induced upwelling. In contrast, in the relatively open seawater of Xisha Island, the MRE is dominated by the East Asian Winter Monsoon, with relatively more negative (lower) ΔR values associated with high wind speeds, implying horizontal transport of seawater. The average SCS ΔR value relative to the Marine20 curve is –161±39 14C years. Our finding highlights the essential role of monsoon in regulating the MRE in the northern SCS, in particularly the tight bond between east Asian winter monsoon and regional MRE.