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Sling configurations significantly influence the coupled dynamics of the helicopter with slung load system (HSLS), resulting in alterations to handling qualities (HQs) that remain inadequately understood. This study introduces a computer-oriented, generalized method for constructing the HSLS model with various sling configurations. To evaluate the HQs of 1-point, 2-point, and 4-point sling configurations, both the stability and response criteria outlined in ADS-33E and a newly proposed criterion for slung loads towards the updated ADS-33F were employed. Modal analysis was conducted to elucidate the coupled mechanisms of the HSLS under different sling configurations. The findings reveal that the dynamics of the main rotor can attenuate the lateral swing motions of the load in the 4-point sling configuration. While multiple-point sling configurations can enhance the helicopter’s bandwidth, they also amplify the magnitude notch in the helicopter’s response. Nevertheless, when a larger hook distance is employed, the notch frequency is sufficiently distant from the load swing bandwidth, leading to a reduced degradation in HQs. A 4-point configuration with lateral and longitudinal hook distances equal to twice the width and length of the slung load is recommended in practice to achieve sufficient swing stability and mitigate HQ degradation.

In order to reveal the mechanism of Category II rotor-body-slung-load coupled oscillation (RBSLCO) with the frequency range of 2.5~8 Hz, a novel nonlinear rigid-elastic coupled model is presented for the helicopter and slung load system (HSLS) with explicit formulation. The slung load system model is coupled with the current rigid-elastic coupled helicopter model, considering fuselage hook point rigid-elastic coupled movements, cable stretching, and hook point force from the slung load system. The results show that carrying the heaviest load is the vital state for Category II RBSLCO. As slung load mass ratio increases, rotor-fuselage coupling becomes stronger and the oscillation frequency shifts slightly, causing a maximum of 15% reduction in stability margin. In addition, even when the load is lightweight, another form of Category II RBSLCO may appear involving fuselage bending and cable stretching. This Category II RBSLCO behaves like the vertical bouncing but is divided into a high-frequency anti-phase oscillation and a relatively low-frequency in-phase oscillation.

Natural organisms have evolved highly sophisticated mechanisms for managing water across a broad range of environmental conditions, from arid to highly humid regions. Among these mechanisms, directional liquid transport (DLT) is particularly noteworthy, as it relies on structural designs that facilitate the spontaneous movement of liquids along predefined pathways without the need for external energy sources. The increasing interest in DLT systems is primarily driven by their potential applications in fields such as microfluidics, water harvesting, and biomedical engineering. The focus on DLT is motivated by its ability to inspire efficient, energy-independent liquid transport technologies, which hold significant promise for both fundamental research and practical applications. Notably, wedge-shaped DLT systems have emerged as a particularly promising area of study due to their advantages in terms of manufacturability, liquid collection efficiency, and scalability—attributes that are essential for industrial deployment. This review seeks to explore natural wedge-based DLT systems, providing an in-depth analysis of their underlying principles and their potential for engineering replication. The discussion includes examples from nature, such as desert beetles and spider silk, and explores the theoretical mechanisms governing these systems, including the role of surface energy gradients and Laplace pressure. Additionally, the review highlights advanced fabrication techniques, such as photolithography and laser micromachining, which are crucial for the development of these systems in practical applications.

This study assesses the influence of engine dynamic characteristics on helicopter handling quality during hover and low-speed forward flight. First, we construct the helicopter–engine coupling model (HECM) based on the power-matching relationship between the engine and the rotor. The impact of the engine is evaluated by comparing HECM with a helicopter model without the engine. To assess the engine’s influence quantitatively, we consider torque response, height response, and collective–yaw coupling characteristics in ADS-33E-PRF handling quality criteria. The results reveal that the engine power output lag can deteriorate the helicopter’s torque and height response handling quality rate (HQR). After the increase in helicopter mass, the torque HQR caused by engine influence improved, and the altitude HQR further deteriorated. The engine dynamic characteristics can also reverse the yaw rate, decreasing collective–yaw coupling HQR. As the helicopter’s flight speed increased, the engine’s impact on the yaw rate increased by 41.8%. This study can provide valuable insight into the effects of engine dynamic characteristics on helicopter handling quality and offer a reference for the design of helicopter–engine coupling control laws.

In order to solve the problems of a slow solving speed and easily falling into the local optimization of an ore-blending process model (of polymetallic multiobjective open-pit mines), an efficient ore-blending scheduling optimization method based on multiagent deep reinforcement learning is proposed. Firstly, according to the actual production situation of the mine, the optimal control model for ore blending was established with the goal of minimizing deviations in ore grade and lithology. Secondly, the open-pit ore-matching problem was transformed into a partially observable Markov decision process, and the ore supply strategy was continuously optimized according to the feedback of the environmental indicators to obtain the optimal decision-making sequence. Thirdly, a multiagent deep reinforcement learning algorithm was introduced, which was trained continuously and modeled the environment to obtain the optimal strategy. Finally, taking a large open-pit metal mine as an example, the trained multiagent depth reinforcement learning algorithm model was verified via experiments, with the optimal training model displayed on the graphical interface. The experimental results show that the ore-blending optimization model constructed is more in line with the actual production requirements of a mine. When compared with the traditional multiobjective optimization algorithm, the efficiency and accuracy of the solution have been greatly improved, and the calculation results can be obtained in real-time.

The Shangfanggou Mo–Fe deposit is a typical and giant porphyry–skarn deposit located in the East Qinling–Dabie molybdenum (Mo) polymetallic metallogenic belt in the southern margin of the North China Block. In this paper, three-dimensional (3D) multi-parameter geological modeling and microanalysis are used to discuss the mineralization and oxidation transformation process of molybdenite during the supergene stage. Meanwhile, from macro to micro, the temporal–spatial–genetic correlation and exploration constraints are also established by 3D geological modeling of industrial Mo orebodies and Mo oxide orebodies. SEM-EDS and EPMA-aided analyses indicate the oxidation products of molybdenite are dominated by tungsten–powellite at the supergene stage. Thus, a series of oxidation processes from molybdenite to tungsten–powellite are obtained after the precipitation of molybdenite; eventually, a special genetic model of the Shangfanggou high oxidation rate Mo deposit is formed. Oxygen fugacity reduction and an acid environment play an important part in the precipitation of molybdenite: (1) During the oxidation process, molybdenite is first oxidized to a MoO2·SO4 complex ion and then reacts with a carbonate solution to precipitate powethite, in which W and Mo elements can be substituted by complete isomorphism, forming a unique secondary oxide orebody dominated by tungsten–powellite. (2) Under hydrothermal action, Mo4+ can be oxidized to jordisite in the strong acid reduction environment at low temperature and room temperature during the hydrothermal mineralization stage. Ilsemannite is the oxidation product, which can be further oxidized to molybdite.

Geometric errors are important factors that affect the accuracy of multi-axis CNC machine tools. In this paper, three aspects of research work are carried out. First, two kinds of error modeling methods are proposed, i.e., tool tip coordinates error modeling (TTC) and kinematic chain transmission error modeling (KCT). This work resolves the theoretical confusion existing in the error modeling process in the past. Second, left matrix multiplication and right matrix multiplication have different meanings for geometric error modeling; this paper makes a detailed analysis and summarizes four identification algorithms for geometric errors based on the above theory. Third, a new R -test device is developed. For the traditional commercial R -test, it is usually difficult to adjust the position and orientation, so it is hard to directly obtain the vectors of the sensor axes and to ensure that the intersection of the sensor axes and the center of precision ball coincide accurately. However, this new R -test with the addition of positioning datums and a sliding table overcomes these problems. The calibration of the R -test is described in detail. Finally, a four-point measurement experiment for identifying the geometric errors of a rotary axis has been conducted, and the effectiveness of the measurement method is verified by a prediction experiment and a comparative experiment of double ball bar (DBB).

Obtaining appropriate temperature sensor locations is crucial for data-driven thermal error modeling. The pseudo-correlation and variable ranking will cause inappropriate sensor selection results. In this paper, a three-step sensor selection strategy based on the detrended cross-correlation coefficient is proposed to obtain a stable and robust set of thermal key points. Combined with sensor reduction and classification, 15 sensors are reduced to 9 and classified into 3 groups. Finally, three sensors are selected as thermal key points. The sensor selection results are applied to a support vector machine model for a CNC grinding machine. The modeling results of 49 predictions based on 7 speed spectrums show that the root mean square error and maximum error are less than 2.32 μm and 3.73 μm, respectively. Compared with two traditional methods, the proposed method has higher accuracy and stronger robustness, which is effective for sensor selection of thermal error modeling.

Chinese herbal medicine (CHM) evolved through thousands of years of practice and was popular not only among the Chinese population, but also most countries in the world. Blumea balsamifera (L.) DC. as a traditional treatment for wound healing in Li Nationality Medicine has a long history of nearly 2000 years. This study was to evaluate the effects of total flavonoids from Blumea balsamifera (L.) DC. on skin excisional wound on the back of Sprague-Dawley rats, reveal its chemical constitution, and postulate its action mechanism. The rats were divided into five groups and the model groups were treated with 30% glycerol, the positive control groups with Jing Wan Hong (JWH) ointment, and three treatment groups with high dose (2.52 g·kg−1), medium dose (1.26 g·kg−1), and low dose (0.63 g·kg−1) of total flavonoids from B. balsamifera. During 10 consecutive days of treatment, the therapeutic effects of rates were evaluated. On day 1, day 3, day 5, day 7, and day 10 after treatment, skin samples were taken from all the rats for further study. Significant increases of granulation tissue, fibroblast, and capillary vessel proliferation were observed at day 7 in the high dose and positive control groups, compared with the model group, with the method of 4% paraformaldehyde for histopathological examination and immunofluorescence staining. To reveal the action mechanisms of total flavonoids on wound healing, the levels of CD68, vascular endothelial growth factor (VEGF), transforming growth factor-β1 (TGF-β1), and hydroxyproline were measured at different days. Results showed that total flavonoids had significant effects on rat skin excisional wound healing compared with controls, especially high dose ones (p < 0.05). Furthermore, the total flavonoid extract was investigated phytochemically, and twenty-seven compounds were identified from the total flavonoid sample by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry/diode array detector (UPLC-Q-TOF-MS/DAD), including 16 flavonoid aglucons, five flavonoid glycosides (main peaks in chromatogram), five chlorogenic acid analogs, and 1 coumarin. Reports show that flavonoid glycoside possesses therapeutic effects of curing wounds by inducing neovascularization, and chlorogenic acid also has anti-inflammatory and wound healing activities; we postulated that all the ingredients in total flavonoids sample maybe exert a synergetic effect on wound curing. Accompanied with detection of four growth factors, the upregulation of these key growth factors may be the mechanism of therapeutic activities of total flavonoids. The present study confirmed undoubtedly that flavonoids were the main active constituents that contribute to excisional wound healing, and suggested its action mechanism of improving expression levels of growth factors at different healing phases.

Capacitive deionization (CDI) with water disinfection materials is an energy-efficient technology for the simultaneous desalination and bio-decontamination of brackish water. However, desalination capacity is always limited by the mechanism of ion electrosorption within the electrical double layer. Recently, the water disinfection ability of CDI has been demonstrated through the functionalization of electrode materials with antimicrobial compounds. To achieve highly efficient and low-cost capacitive deionization and disinfection (CDID) performance, we propose a facile strategy for the fabrication of a graphene oxide/polyaniline/Prussian blue (GO/PANI/PB) nanocomposite. This nanocomposite exhibits a high Brunauer–Emmett–Teller surface area (148.08 m 2 g −1 ), mesopore volume (34.02 cm 3 g −1 ), and pore volume (0.66 cm 3 g −1 ), making it suitable as a Faradaic electrode in the CDI and CDID systems. The obtained GO/PANI/PB electrode exhibits a high desalination capacity of 91.6 mg g −1 and superior desalination ratio of 3.05 mg g −1 min −1 at 1 A g −1 . Furthermore, the GO/PANI/PB electrode has a bacterial ( Escherichia coli ) removal and inactivation efficiency of 94.0% ± 3.1% without the use of other disinfectants. This is ∼7 times higher than the antibacterial efficiency of active carbon electrodes under the same CDI conditions. The proposed strategy is the first to exploit simultaneous deionization and disinfection without using disinfectants, offering the potential of using PB-based Faradaic electrodes for eco-friendly and high-efficiency water desalination and disinfection in future CDID technology.