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The current type synthesis of the redundant actuated parallel mechanisms is adding active-actuated kinematic branches on the basis of the traditional parallel mechanisms, or using screw theory to perform multiple getting intersection and union to complete type synthesis. The number of redundant parallel mechanisms obtained by these two methods is limited. In this paper, based on Grassmann line geometry and Atlas method, a novel and effective method for type synthesis of redundant actuated parallel mechanisms (PMs) with closed-loop units is proposed. Firstly, the degree of freedom (DOF) and constraint line graph of the moving platform are determined successively, and redundant lines are added in constraint line graph to obtain the redundant constraint line graph and their equivalent line graph, and a branch constraint allocation scheme is formulated based on the allocation criteria. Secondly, a scheme is selected and redundant lines are added in the branch chains DOF graph to construct the redundant actuated branch chains with closed-loop units. Finally, the branch chains that meet the requirements of branch chains configuration criteria and F&C (degree of freedom & constraint) line graph are assembled. In this paper, two types of 2 rotational and 1 translational (2R1T) redundant actuated parallel mechanisms and one type of 2 translational and 1 rotational (2T1R) redundant actuated parallel mechanisms with few branches and closed-loop units were taken as examples, and 238, 92 and 15 new configurations were synthesized. All the mechanisms contain closed-loop units, and the mechanisms and the actuators both have good symmetry. Therefore, all the mechanisms have excellent comprehensive performance, in which the two rotational DOFs of the moving platform of 2R1T redundant actuated parallel mechanism can be independently controlled. The instantaneous analysis shows that all mechanisms are not instantaneous, which proves the feasibility and practicability of the method.

In the field of intelligent manufacturing, image anomaly detection plays a pivotal role in automated product quality inspection. Most existing anomaly detection methods are adept at capturing local features of images, achieving high detection accuracy for structural anomalies such as cracks and scratches. However, logical anomalies typically appear normal within local regions of an image and are difficult to represent well by the anomaly score map, requiring the model to possess the capability to extract global context features. To address this challenge while balancing the detection of both structural and logical anomalies, this paper proposes a lightweight anomaly detection framework built upon EfficientAD. This framework integrates the reconstruction difference constraint (RDC) and a logical anomaly detection module. Specifically, the original EfficientAD relies on the coarse-grained reconstruction difference between the student and the autoencoder to detect logical anomalies; but, false detection may be caused by the local fine-grained reconstruction difference between the two models. RDC can promote the consistency of the fine-grained reconstruction between the student and the autoencoder, thereby effectively alleviating this problem. Furthermore, in order to detect anomalies that are difficult to represent by feature maps more effectively, the proposed logical anomaly detection module extracts and aggregates the context features of the image, and combines the feature-based method to calculate the overall anomaly score. Extensive experiments demonstrate our method’s significant improvement in logical anomaly detection, achieving 94.2 AU-ROC on MVTec LOCO, while maintaining strong structural anomaly detection performance at 98.4 AU-ROC on MVTec AD. Compared to the baseline, like EfficientAD, our framework achieves a state-of-the-art balance between both anomaly types.

With the development of fluid-power transmission and control technology, electro-hydraulic-driven technology can significantly improve the load-carrying capacity, stiffness, and control accuracy of stabilization platforms. However, compared with mechanically driven platforms, the stiffness and damping of the fluid, as well as the coupling effect between the fluid and the structure need to be considered for electro-hydraulic-driven parallel stabilization platforms, making the modal and dynamic response characteristics of the mechanism more complex. With the aim of solving the aforementioned issues, we research the electro-hydraulic driven 3-UPS/S parallel stabilization platform considering the hinge stiffness. Moreover, the characteristic vibration equation of the mechanism is established using the virtual work principle. Subsequently, the variation characteristics of the natural frequency and the vibration response according to the position of the mechanism are analyzed based on the dynamic equation. Finally, the correctness of the model is verified by a modal test and Runge-Kutta methods. This study provides a theoretical basis for the dynamic design of electrohydraulic-driven parallel mechanisms.

Cold atmospheric plasma (CAP), a novel promising anti-cancer modality, has shown its selective anti-cancer capacity on dozens of cancer cell lines in vitro and on subcutaneous xenograft tumors in mice. Over the past five years, the CAP-stimulated solutions (PSS) have also shown their selective anti-cancer effect over different cancers in vitro and in vivo . The solutions used to make PSS include several bio-adaptable solutions, mainly cell culture medium and simple buffered solutions. Both the CAP-stimulated medium (PSM) and the CAP-stimulated buffered solution (PSB) are able to significantly kill cancer cells in vitro . In this study, we systematically compared the anti-cancer effect of PSM and PSB over pancreatic adenocarcinoma cells and glioblastoma cells. We demonstrated that pancreatic cancer cells and glioblastoma cells were specifically vulnerable to PSM and PSB, respectively. The specific response such as the rise of intracellular reactive oxygen species of two cancer cell lines to the H 2 O 2 -containing environments might result in the specific vulnerabilities to PSM and PSB. In addition, we demonstrated a basic guideline that the toxicity of PSS on cancer cells could be significantly modulated through controlling the dilutability of solution.

Autophagy degrades phagocytosed damaged organelles, misfolded proteins, and various pathogens through lysosomes as an essential way to maintain cellular homeostasis. Autophagy is a tightly regulated cellular self-degradation process that plays a crucial role in maintaining normal cellular function and homeostasis in the body. The NLRP3 inflammasome in neuroinflammation is a vital recognition receptor in innate cellular immunity, sensing external invading pathogens and endogenous stimuli and further triggering inflammatory responses. The NLRP3 inflammasome forms an inflammatory complex by recognizing DAMPS or PAMPS, and its activation triggers caspase-1-mediated cleavage of pro-IL-1β and pro-IL-18 to promote the inflammatory response. In recent years, it has been reported that there is a complex interaction between autophagy and neuroinflammation. Strengthening autophagy can regulate the expression of NLRP3 inflammasome to reduce neuroinflammation in disease and protect neurons. However, the related mechanism is not entirely clear. The formation of protein aggregates is one of the common features of Alzheimer's diseases(AD) and Parkinson's diseases(PD). A large number of toxic protein aggregates can induce inflammation. In theory, activation of the autophagy pathway can remove the potential toxicity of protein aggregates and delay the progression of the disease. This article aims to review recent research on the interaction of autophagy, NLRP3 inflammasome, and protein aggregates in and PD, analyze the mechanism, and provide theoretical reference for further primary research in the future.

Background China is ranked third globally in terms of burden and has a moderately high to high prevalence of tuberculosis (TB). This study meticulously investigated the notification rates of TB and assessed the epidemic in China from 2000 to 2021. The aim of the study was to provide robust supporting data that is crucial for enhancing TB prevention and control strategies. Methods Extensive data regarding TB notification rates in China between 2000 and 2021 was collected. The joinpoint regression model was subsequently utilized to assess the temporal trends in the notification rates of TB, which were analyzed through the annual percentage change (APC) and the average annual percentage change (AAPC). Results During the study period (2000–2021), the standardized notification rates of TB in China ranged from 38.89/100,000 to 101.15/100,000, with a significant annual average decrease of 4.43% ( P  < 0.05). Before the COVID-19 pandemic, a marked acceleration in this decline was observed from 2006 to 2015, with an APC of 4.62% ( P  < 0.05). Stratified by age and sex, the age group with the most significant annual decline in overall standardized notification rates of TB among males in China was < 15 years old, followed by 55–64 years old, and the group with the least decrease was 25–44 years old. Similarly, the age group with the most significant annual decline in standardized notification rates of TB among females was < 15 years old. Conclusions The epidemic of TB in China exhibited a downward trajectory between 2000 and 2021. However, it is imperative to prioritize the attention given to males and older adults, and to promote specific and effective prevention and control strategies for these populations.

Although soil moisture is a key factor of hydrologic and climate applications, global continuous high resolution soil moisture datasets are still limited. Here we use physics-informed machine learning to generate a global, long-term, spatially continuous high resolution dataset of surface soil moisture, using International Soil Moisture Network (ISMN), remote sensing and meteorological data, guided with the knowledge of physical processes impacting soil moisture dynamics. Global Surface Soil Moisture (GSSM1 km) provides surface soil moisture (0–5 cm) at 1 km spatial and daily temporal resolution over the period 2000–2020. The performance of the GSSM1 km dataset is evaluated with testing and validation datasets, and via inter-comparisons with existing soil moisture products. The root mean square error of GSSM1 km in testing set is 0.05 cm 3 /cm 3 , and correlation coefficient is 0.9. In terms of the feature importance, Antecedent Precipitation Evaporation Index (APEI) is the most important significant predictor among 18 predictors, followed by evaporation and longitude. GSSM1 km product can support the investigation of large-scale climate extremes and long-term trend analysis.

Existing models of bulk modulus for aerated hydraulic fluids primarily focus on the effects of pressure and air fraction, whereas the effect of temperature on bulk modulus is disregarded. Based on the lumped parameter method and the full cavitation model, combined with the improved Henry’s law and the air polytropic course equation, a theoretical model of dynamic bulk modulus for an aerated hydraulic fluid is derived. The effects of system pressure, air fraction, and temperature on bulk modulus are investigated using the controlled variable method. The results show that the dynamic bulk modulus of the aerated hydraulic fluid is inconsistent during the compression process. At the same pressure point, the dynamic bulk modulus during expansion is higher than that during compression. Under the same initial air faction and pressure changing period, a higher temperature results in a lower dynamic bulk modulus. When the pressure is lower, the dynamic bulk modulus of each temperature point is more similar to each other. By comparing the theoretical results with the actual dynamic bulk modulus of the Shell Tellus S ISO32 standard air-containing oil, the goodness-of-fit between the theoretical model and experimental value at three temperatures is 0.9726, 0.9732, and 0.9675, which validates the theoretical model. In this study, a calculation model of dynamic bulk modulus that considers temperature factors is proposed. It predicts the dynamic bulk modulus of aerated hydraulic fluids at different temperatures and provides a theoretical basis for improving the analytical model of bulk modulus.

As a by-product of phosphate fertilizer production, phosphogypsum (PG) poses pressing environmental challenges that demand urgent resolution. To address the research gap in dynamic impact behavior of PG-modified concrete (PGC), this study developed truss-reinforced PGC slabs (PG volumetric fractions: 0% and 2%) and evaluated their impact resistance through drop-weight tests from a 3.75 m height. A systematic parametric investigation was conducted to quantify the effects of slab thickness (100–120 mm), steel plate reinforcement at the tension zone, PG content, and impact cycles. Experimental results revealed that increasing slab thickness to 120 mm reduced mid-span displacement by 13%, while incorporating steel plate reinforcement provided an additional 5.3% reduction. Notably, PG addition effectively suppressed crack propagation, transitioning failure modes from radial fracture patterns to localized mid-span damage. Finite element modeling ABAQUS (2022) validated experimental observations, demonstrating strong agreement. While optimized PG dosage (2%) exhibited limited influence on impact resistance, it enhanced PG utilization efficiency by 18%. Combined with increased slab thickness (displacement reduction: 13%), this study establishes a design framework balancing environmental sustainability and structural reliability for impact-resistant PGC applications. Within the framework of truss-reinforced concrete slabs with constant PG dosage, this study established a numerical model for geometric parameter modulation of impactors. Through systematic adjustment of the drop hammer’s contact width (a) and vertical geometric height (h), a dimensionless control parameter—aspect ratio c = h/a (0.2 ≤ c ≤ 1.8)—was proposed. Nonlinear dynamic analysis revealed that the peak impact load demonstrates an inverse proportional functional decay relationship with increasing c, yielding an empirical predictive model. These parametrized regularities provide theoretical foundations for contact interface optimization in impact-resistant structural design.

Meteorological disasters frequently occur in China and around the world. These natural hazards can cause huge economic losses and threaten the personal safety of citizens. The public’s willingness to engage with disaster relief efforts and the degree of participation is critical to reduce the impact of such disasters. This study conducted a survey with 62,903 respondents from China. The study utilized statistical analysis and correlation analysis in order to understand the differences and similarities of the public’s willingness to take part in disaster relief across gender and age. The study found that: (1) the public’s awareness of insurance and willingness to make donations during climate disasters is low, and that more than half of the public are only willing to insure for very less money; (2) although the public has very high enthusiasm to participate in disaster relief, they are less willing to learn the basic skills of reducing disasters and for participating in training for disaster reduction as volunteers. This was especially the case for elderly citizens and females; (3) the willingness of the public to prevent and reduce disasters is high, and this was the case across various gender and age groups. Finally, the study puts forward several measures to improve the uptake of disaster relief and disaster prevention among citizens.