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The ocean offers abundant wind and wave energy resources. This paper proposes an integrated concept that co-locates a semi-submersible floating wind platform with wave energy converters (WECs) to exploit the geographical consistency of these resources. By sharing the platform foundation and power transmission infrastructure, this integrated system enhances the utilization efficiency of marine space and renewable energy. Inspired by the principles of the Tuned Mass Damper (TMD) and leveraging mature hydraulic technologies from wave energy conversion and offshore drilling heave compensation systems, this study introduces a novel scheme. This scheme integrates a heave plate with a hydraulic Power Take-Off (PTO) system, functionally acting as a wave energy converter, to the floating platform. The primary objective is to mitigate the platform’s motion response while simultaneously generating electricity. The research investigates the motion performance improvement of this integrated platform under South China Sea conditions. The results demonstrate that the proposed WEC–PTO system not only improves the platform’s wave resistance and adaptability to deep-sea environments but also increases the overall efficiency of marine energy equipment deployment.

This paper investigates bearing-based formation control of multiple unmanned aerial vehicles (UAVs) flying in low-altitude wind fields. In such environments, time-varying wind disturbances can distort the formation geometry, enlarge bearing errors, and even induce potential collisions among neighboring UAVs, yet they also contain components that can be beneficial for the formation motion. Conventional disturbance compensation methods treat wind as a purely harmful factor and aim to reject it completely, which may sacrifice responsiveness and energy efficiency. To address this issue, we propose a pure bearing-based formation control framework with Conditional Disturbance Utilization (CDU). First, a real-time disturbance observer is designed to estimate the wind-induced disturbances in both translational and rotational channels. Then, based on the estimated disturbances and the bearing-dependent potential function, CDU indicators are constructed to judge whether the current disturbance component is beneficial or detrimental with respect to the formation control objective. These indicators are embedded into the bearing-based formation controller so that favorable wind components are exploited to accelerate formation convergence, whereas adverse components are compensated. Using an angle-rigid formation topology and a Lyapunov-based analysis, we prove that the proposed CDU-based controller guarantees global asymptotic stability of the desired formation. Simulation results on triangular and hexagonal formations under complex wind disturbances show that the proposed method achieves faster convergence and improved responsiveness compared with traditional disturbance observer-based control, while preserving formation stability and safety.

STAM Binding Protein Like 1 (STAMBPL1), functions as a deubiquitinase (DUB) and plays a significant role in various types of cancers. However, its effect as a DUB participating in the HCC tumorigenesis and progression still unknown. In the study, the upregulation and strong prognosis value of STAMBPL1 were identified in HCC patients. Functionally, STAMBPL1 significantly promoted HCC cells proliferation and metastasis, and it interacts with TRAF2 and stabilize it via the deubiquitination at the K63 residue. The TRAF2 upregulation stabilized by STAMBPL1 overexpression transfers of P65 protein into the nucleus and activates the WNT/PI3K/ NF-kb signaling pathway. The 251–436 sites of STAMBPL1 particularly interact with the 294–496 sites of TRAF2, thereby exerting the function of DUB and removing the ubiquitin molecules attached to TRAF2. Our research unveiled a new function of STAMBPL1 in mediating TRAF2 deubiquitination and stabilization, thereby activating the WNT/PI3K/NF-kb signaling pathway, suggesting its potential as a novel biomarker and therapeutic target for HCC.

This paper presents a distributed adaptive formation control strategy for a multiple near-space vehicles (NSVs) system operating under unknown input constraints and external disturbances. In challenging near-space environments, the control system must address not only model uncertainties and parameter variations but also accommodate the input limitations of actuators. To address these challenges, we design an adaptive distributed formation control strategy for vehicle formation that relies exclusively on relative attitude information. This approach is grounded in the principles of angle rigidity formation theory, which has not previously been applied in the near-space vehicle domain. The aim of the adaptive formation control strategy is to maintain the desired formation shape for the near-space vehicles (NSVs) system with external disturbances, actuator dead zones, and saturation. In addition, neural networks are employed to approximate the inherent nonlinear uncertainties within the NSV models. An adaptive estimation technique is concurrently included to address parameter variations and to alleviate the impact of external disturbances, actuator dead zones, and saturation effects. Finally, a Lyapunov-based analysis is used to rigorously demonstrate the stability of the NSV formation system. The simulation results validate the effectiveness and robustness of the proposed control strategy in uncertain environments.

The net shell is a widely utilized large-span space structure known for its aesthetically pleasing design and uniform load distribution, as well as serving as a prominent architectural landmark. In recent years, the impact resistance research of mesh and shell structures has garnered increased attention due to the accumulation of local conflicts. In this study, a parametric model of the spherical mesh shell was developed with Rhino software, and a numerical analysis model for a K8 mesh shell was established through the application of the ABAQUS finite element analysis software. Subsequently, the proposed numerical analysis method for the impact test was applied to validate its accuracy. The research also explored various dynamic constitutive models, such as Cowper-Symonds, Johnson-Cook, modified temperature term Johnson-Cook, and modified strain term and temperature term Johnson-Cook, with the assessment of their impact on the numerical simulation of impact resistance. Based on the impact dynamic response of the spherical net shell of different materials, the selection of an appropriate dynamic constitutive model for the numerical simulation of impact resistance in the spherical net shell was the MJ-C model. The comparative analysis of different materials, including Q235B, Q355B, Q460D, and 6061-T6, indicated that when the impact material failed to penetrate the structure instantly, the improvement of the material strength would enhance the impact resistance of the structure. On the other hand, when the impact material managed to penetrate the structure instantly, the material strength would not significantly help mitigate the damage. Notably, brittle materials, such as aluminum alloy, exhibited a distinct absence of a pronounced yield stage compared with low-carbon steel, which ultimately led to a relatively abrupt deformation.

Three-dimensional (3D) printing is an innovative manufacturing process based on 3D digital models that involves layer-by-layer addition of materials. In recent years, 3D printing has made good progress in the field of construction, thereby leading to more stringent requirements for materials. In this study, we first compare different equipment and materials used for 3D printing concrete. Subsequently, the mix ratio of extruded and cured 3D printed concrete is studied by using flow and slump as the main evaluation indexes. Through a universal test, the influence of different dosages of water reducer, retarder, and latex powder on the performance of 3D printed concrete (compression resistance strength) is studied. Furthermore, the optimum mix ratio for fiber reinforced concrete is determined, based on which axial pull-out, axial compression, and three-point bending tests are performed to elucidate the peak compressive strength, load–displacement curve, and mechanical properties of 3D printed concrete. By employing the ABAQUS finite element software, the shaft pulling force and axial compression of 3D printed concrete are simulated and analyzed to determine the parameters influencing the bonding performance of different 3D printed concrete layers. Moreover, the influence of water reducer and sand–glue ratio is observed to be greater than that of water gel ratio and sodium gluconate. The testing results showed that the mechanical strength of 3D printed concrete is lower than that of poured concrete. Meanwhile, bending and compressive strengths of 3D printed concrete and poured concrete are quite different.

Keloids and hypertrophic scars are fibroproliferative disorders with high recurrence rates, lacking a definitive treatment standard. This review systematically evaluates current therapies and their effectiveness in treating keloid and hypertrophic scars. The inclusion criteria were based on the population, intervention, comparator, outcomes, and study design (PICOS) framework. Electronic searches through April 2025 across databases such as PubMed, EMBASE, Cochrane Library, and Web of Science used keywords such as 'keloid', 'occlusive dressings', and 'imiquimod', among others. Meanwhile, we used the keywords and to search for molecular mechanisms associated with keloid and hypertrophic scars. The Risk of Bias 2 (RoB2) and Methodological Index for Non-Randomized Studies (MINORS) checklists were used to assess the quality of the included studies and potential bias. This study synthesizes findings from 162 studies, exploring a range of treatments including monotherapies and combination therapies, such as local corticosteroid injections, optical therapy, radiation therapy, 5-fluorouracil (5-FU) therapy, bleomycin therapy, verapamil therapy, excision surgery, cryotherapy, and topical treatments, as well as various multi-drug regimens. It also examines innovative therapies such as stem cells and RNA microneedles. Technological developments continue to expand the range of available interventions. Treatment strategies increasingly emphasized combination therapies that integrate intralesional corticosteroids, surgical excision, laser modalities, and radiotherapy, demonstrating superior outcomes compared with single-modality approaches, particularly in reducing recurrence, prolonging therapeutic benefit, and improving patient prognosis. Sole treatments and inadequate therapy are major risk factors for recurrence. Anti-fibroblast growth strategies are crucial, aside from physical interventions. Despite the lack of an established gold standard, corticosteroid and excision therapies remain critical benchmarks for evaluating new treatments.

Background At present, the proportion of undiagnosed diabetes in Chinese adults is as high as 15.5%. People with diabetes who are not treated and controlled in time may have various complications, such as cardiovascular and cerebrovascular diseases and diabetic foot disorders, which not only seriously affect the quality of life of people with diabetes but also impose a heavy burden on families and society. Therefore, prevention and control of type 2 diabetes is of great significance. Methods We constructed a logistic regression model, a neural network model and a decision tree model to analyse the risk factors for type 2 diabetes and then compared the prediction accuracy of the different models by calculating the area under the relative operating characteristic (ROC) curve and back-inputting the data into the model. Results The prevalence of type 2 diabetes in 4177 subjects who were not diagnosed with type 2 diabetes was 9.31%. The most influential factors associated with type 2 diabetes were triglyceride (TG) ≥ 1.17 mmol/L (odds ratio (OR) =2.233), age ≥ 70 years (OR = 1.734), hypertension (OR = 1.703), alcohol consumption (OR = 1.674), and total cholesterol≥5.2 mmol/L (TC) (OR = 1.463). The prediction accuracies of the three prediction models were 90.8, 91.2, and 90.7%, respectively, and the areas under curve (AUCs) were 0.711, 0.780, and 0.698, respectively. The differences in the AUCs after back propagation (BP) of the neural network model, logistic regression model and decision tree model were statistically significant ( P  < 0.05). Conclusion BP neural networks have a higher predictive power for identifying the associated risk factors of type 2 diabetes than the other two models, but it is necessary to select a suitable model for specific situations.

By using straw to build an assembled flood wall, this study provided new ideas for useful applications of straw and for the development of assembly flood control facilities. A straw flexible space assembly flood control system is designed on the basis of Revit, and a hydraulic test of a scaled-down model of the system is conducted using a water-retaining test machine to prove the stability and impact resistance of the system. Finally, a numerical analysis model of the straw flexible space flood control system is established using ABAQUS software to perform finite element analysis of the system. A comparison of the test results and the numerical analysis results shows that they can be well fitted. Thus, this study lays a theoretical foundation for a large-scale engineering application of the proposed system.

Background To explore the risk factors of coexisting prediabetes and prehypertension, to provide theoretical basis for early intervention. Methods A multi-stage stratified random cluster sampling method was used to randomly select adult residents from Jilin Province in 2013 for questionnaire surveys, physical examinations, and laboratory tests. Results The prevalence of coexisting prediabetes and prehypertension in Jilin Province was 11.3%. The binary Logistic regression results showed that age, sex, education, triglyceride (TG), BMI, waist circumference and alcohol consumption were the effects of factor coexisting prediabetes and prehypertension. Conclusion It is important to pay attention to the early stage of hypertension and diabetes, control the transition from prehypertension and prediabetes to hypertension and diabetes, and improve the health of residents.