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To reduce the inaccuracy of using the monitoring data outside the pit to evaluate the unorganized emission dust source of open pit mine, the circulating accumulation emission model is established. Based on the model, the monitoring data in the pit can be converted into the dust emission from the pit. The main conclusions include: (1) the circulating accumulation emission model is suitable for the dust diffusion process in open pit mine. The ratio of diffusion μ and the ratio of surplus ε were used to simulate the dust diffusion process in open pit mine, containing emission, retention and diffusion. (2) The initial value of the dust in the pit before the team operation has little influence on the final stable value. (3) When the external dust enters the pit, it will accumulate under the action of eddy current. The dust background value in the pit is different from that outside the pit. (4) The dust emission from the pit can be calculated from the monitoring data in the pit based on the circulating accumulation emission model. The model can deal with environmental changes such as the wind direction and speed, without arranging a lot of external monitoring equipment like the traditional external monitoring methods.

Flutter is a self‐excited vibration under the interaction of the inertial force, aerodynamic force, and elastic force of the structure. After the flutter occurs, the aircraft structures will exhibit limit cycle oscillation, which will cause catastrophic accidents or fatigue damage to the structures. Therefore, it is of great theoretical and practical significance to study the aeroelastic characteristics and flutter control for improving the aeroelastic stability of aircraft structures. This paper reviews the recent advances in aeroelastic analysis and flutter control of wings and panel structures. The mechanism of aeroelastic flutter of wings and panels is presented. The research methods of aeroelastic flutter for different structures developed in recent years are briefly summarized. Various control strategies including the linear and nonlinear control algorithms as well as the active flutter control results of wings and panels are presented. Finally, the paper ends with conclusions, which highlight challenges of the development in aeroelastic analysis and flutter control, and provide a brief outlook on the future investigations. This study aims to present a comprehensive understanding of aeroelastic analysis and flutter control. It can also provide guidance on the design of new wings and panel structures for improving their aeroelastic stability.

The ultrasonic frequency radial vibration of an elastic thin spherical shell composed of isotropic materials is studied, the frequency equation of its vibration is deduced, and the equivalent circuit is obtained. The finite element software COMSOL is used to verify the obtained analytical theory, and the calculated results are basically consistent with the theoretical calculated values. The relevant conclusions provide references for the application of spherical shell structure in related fields.

This paper presents an improved design to address the issue of elevator jamming in aircraft. The proposed solution involves an auxiliary spare tail system, featuring a foldable spare tail unit integrated with the primary empennage, which is extended in emergency situations. Deflection of this spare tail is designed to generate an additional pitching moment, thereby providing a measure of pitch control for the aircraft. Both the primary and spare tail surfaces utilize the NACA0012 airfoil. The Spalart-Allmaras turbulence model was selected for the simulations, which were conducted at a freestream Mach number of 0.6. Computational Fluid Dynamics (CFD) simulations, employing a dynamic mesh technique, were performed to analyze the aerodynamic behavior of the tail system during an elevator jamming scenario. The results indicate that the deployment and appropriate deflection of the spare tail can generate sufficient additional pitching moment, effectively mitigating the loss-of-control problem resulting from an elevator malfunction.

Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55-89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77-96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80-4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80-96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82-93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45-99.98) and GMT (SMD 6.20, 95% CI: 2.02-10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38-1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups ( > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

Proteolysis-targeting chimeras (PROTACs) present a potentially effective strategy against various diseases via selective proteolysis. How to increase the efficacy of PROTACs remains challenging. Here, we explore the necessity of the linker, which has been deemed as an integral part of heterobifunctional PROTACs. Adopting single amino acid-based degradation signals, we find that the linker is not a required feature of the PROTACs. Notably, the linker-free PROTAC, Pro-BA, exhibits superior efficacy over its linker-bearing counterparts in degrading EML4-ALK and inhibiting lung cancer cell growth, as Pro-BA induces a stronger interaction between the target and the E3 ubiquitin ligase. Pro-BA is a water-soluble, orally administered degrader that significantly inhibits the tumor growth in a xenograft mouse model. The broad applicability of this linker-free PROTAC strategy is further validated through the development of BCR-ABL degrader. Our study introduces a design paradigm for PROTACs, potentially facilitating the advancement of more efficient therapeutic degraders. Linkers are traditionally seen as important for PROTAC activity. Here, the authors demonstrate that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.

A robot screwing skill learning framework based on teaching–learning is proposed to improve the generalization ability of robots for different scenarios and objects, combined with the experience of a human operation. This framework includes task-based teaching, learning, and summarization. We teach a robot to twist and gather the operation’s trajectories, define the obstacles with potential functions, and counter the twisting of the robot using a skill-learning-based dynamic movement primitive (DMP) and Gaussian mixture model–Gaussian mixture regression (GMM-GMR). The hole-finding and screwing stages of the process are modeled. In order to verify the effectiveness of the robot tightening skill learning model and its adaptability to different tightening scenarios, obstacle avoidance trends and tightening experiments were conducted. Obstacle avoidance and tightening experiments were conducted on the robot tightening platform for bolts, plastic bottle caps, and faucets. The robot successfully avoided obstacles and completed the twisting task, verifying the effectiveness of the robot tightening skill learning model and its adaptability to different tightening scenarios.

Due to the alternating loads on pumping units and the integration of new energy sources, multisource DC microgrid pumping unit well groups experience increased fluctuations in voltage and power as well as superimposed peak and valley values. This work presents a distributed control strategy for pumping unit well groups on a multisource DC microgrid based on the weighted moving average algorithm. A centralized control program is implanted in the RTU of the single-well controller of each pumping unit, and communication with each well is realized via SCADA and multicast communication, resulting in a distributed well group system. The real-time power values of the pumping well group are calculated by grouping the power values, and each group is weighted using the total power fluctuation threshold of the well group as the control target. Then, a weighted moving average algorithm is used to predict the next power value and form a table of predicted real-time power spectra. According to the power values in the community power spectrum table, the inverter frequency is proportionally adjusted downwards to reach the power peak before deceleration; after the power peak is crossed, the frequency is increased in the same way to reach the power valley before acceleration. Finally, the peak and valley power values of the bus system level off and further learn to reach the set impulse; ultimately, a stable impulse is formed. In laboratory testing and field application in the Shengli Oilfield XIN-11 block, the group control software module effectively suppressed the active power peak and valley values and voltage fluctuations of the bus system, the active power fluctuation rate range decreased by more than 70%, and the DC bus voltage fluctuation range decreased by more than 80%; moreover, the active power decreased by approximately 6% without additional hardware costs.

This study reveals lipidomic adaptations in camel milk that are crucial for neonatal development in desert environments. Using UHPLC-MS/MS and targeted oxylipidomics, we compared milk from free-grazing camels and cows from the same region. We identified 2460 lipids across 44 subclasses and 11 oxygenated lipids in three groups. Glycerophospholipids (GP) were dominant in both. We found 498 differentially expressed lipids, including potential biomarkers such as phosphatidylinositol (PI 18:0/22:3), phosphatidylethanolamine (PE 18:0/22:3), and two triacylglycerol (TG) species. Camel milk was dominated by phosphatidylcholine (PC, approximately 49%) and PI (approximately 22%), whereas cow milk was predominantly composed of TG (nearly 98%). Pathway analysis showed 11 key altered lipid pathways, mainly glycerophospholipid metabolism. These results define camel milk’s unique lipid profile—linked to desert adaptation—and provide molecular insights into its role in supporting neonatal camels in arid environments.

At present, the production lines of mobile phones are mainly manual and semi-automatic. Robots are the most important tools used to improve the intelligence level of industry production. The design of an intelligent robotic assembly system is presented in this paper, which takes the assembly of screen components and shell components as examples. There are major factors restricting the application of robots, such as the calibration of diversified objects, the moving workpiece with incomplete information, and diverse assembly types. A method was proposed to solve these technological difficulties. The multi-module calibration method is used to transform the pose relationship between the robot, the conveyor belt, and the two cameras in the robot assembly system. Aiming at a workpiece moving with incomplete information, the minimum matrix method is proposed to detect the position. Then dynamic fetching is realized based on pose estimation of the moving workpiece. At last, the template matching method is used to identify the assembly area of the workpiece type. The proposed method was verified on a real platform with a LINKHOU LR4-R5 60 robot. Results showed that the assembly success rate was above 98%, and the intelligent assembly system of the robot can realize the assembly of mobile phone screens and back shells without any staff.