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The continuous enhancement of optimization algorithms and their parameters has spurred the expansion of AI into novel application domains such as image recognition and smart home technology. This paper employs the system response curve (SRC) to the adaptive learning rate optimizer, addressing challenges associated with the establishment of the optimizer control model and parameter adjustments affecting the dynamic performance of the system. These insights offer theoretical support for the optimizer's application in deep learning models. To begin, the adaptive learning rate optimizer is a time‐varying system. Based on the intrinsic relationship between the network optimization and the control system, the time domain expression and approximate transfer function of the adaptive learning rate optimizer are derived, and the system dynamic model is established. Furthermore, based on the system control model of the optimizer, it is proposed to explain the performance impacts of different optimizers and their hyperparameters on the deep learning model through the SRC. Finally, experiments are performed on the MNIST, CIFAR‐10, UTKinect‐Action3D, and Florence3D‐Action datasets to validate the control theory of explaining optimizers through system response curves. The experimental results show that the recognition performance of the Adaptive Moment Estimate (Adam) is better than that of the Adaptive Gradient (AdaGrad) and Root Mean Square Propagation (RMSprop). Additionally, the learning rate affects the model training speed, and the practical application aligns with the theoretical analysis. [ABSTRACT FROM AUTHOR]

AbstractIn this study, a dynamic model of a 3-D 4-directional braided composite plate with large overall motions is proposed. Based on the Kirchhoff’s plate hypothesis, the deformation of the orthotropic plate is described. The assumed mode method is employed to discretize the displacement variables, and the rigid-flexible coupled dynamic model of the plate is derived from the Lagrange equation. The equivalent stiffness matrices of 3-D 4-directional braided composites with different braided angles are obtained using the homogenization method. The effects of different velocities and braided angles on the dynamic characteristics of the plate with translational motion and fixed-axis rotation, respectively, are investigated. The present study lays the theoretical foundation for analyzing the dynamic properties of orthotropic plates in engineering components. For example, the dynamic model established in this study can be used to estimate the dynamic responses of braided composite parts in aeronautical structures. [ABSTRACT FROM AUTHOR]

Real-world robotic operations often face uncertainties that can impede accurate control of manipulators. This study proposes a recurrent neural network (RNN) combining kinematic and dynamic models to address this issue. Assuming an unknownmassmatrix, the proposedmethod enables e [ABSTRACT FROM AUTHOR]

Summary: The dynamic ranking, due to its increasing importance in many applications, is becoming crucial, especially with the collection of voluminous time‐dependent data. One such application is sports statistics, where dynamic ranking aids in forecasting the performance of competitive teams, drawing on historical and current data. Despite its usefulness, predicting and inferring rankings pose challenges in environments necessitating time‐dependent modelling. This paper introduces a spectral ranker called Kernel Rank Centrality, designed to rank items based on pairwise comparisons over time. The ranker operates via kernel smoothing in the Bradley–Terry model, utilising a Markov chain model. Unlike the maximum likelihood approach, the spectral ranker is nonparametric, demands fewer model assumptions and computations and allows for real‐time ranking. We establish the asymptotic distribution of the ranker by applying an innovative group inverse technique, resulting in a uniform and precise entrywise expansion. This result allows us to devise a new inferential method for predictive inference, previously unavailable in existing approaches. Our numerical examples showcase the ranker's utility in predictive accuracy and constructing an uncertainty measure for prediction, leveraging data from the National Basketball Association (NBA). The results underscore our method's potential compared with the gold standard in sports, the Arpad Elo rating system. [ABSTRACT FROM AUTHOR]

A method utilizing an embedded sensing system to determine the dynamic load is proposed to address the problem of not being able to directly obtain the dynamic load time history of a crawler driving structure in the harsh underground working environment of a coal mine roadheader robot. A crawler driving structure and its embedded sensing system are designed. A rigid–flexible coupling simulation model of the roadheader robot is established, and the dynamic load time history parameters of the crawler obtained from the simulation and test data are compared and analyzed. Results show that the load fluctuation of the tested track plate at the idler and sprocket is significant. By contrast, the fluctuation of the free segment is minimal. The load fluctuation range of the support segment of the hard road is −5–15 MPa, and that of the soft sand road is −10–25 MPa. Moreover, the track plate exhibits noticeable warping and winding phenomenon relative to the road wheel on the soft sand road. The changing trend of the crawler dynamic load time history obtained from simulation and test is relatively consistent. This study provides a reference for the crawler driving structure's structural optimization and reliability research. [ABSTRACT FROM AUTHOR]

In order to grasp dynamic characteristics of the kind of high-speed structural redundant parallel manipulator in actual work, the dynamic response of a novel high-speed structural redundant parallel manipulator considering multiple spatial revolute joints with radial and axial clearances is studied. Firstly, the dynamic model of the novel high-speed parallel manipulator considering the multiple spatial revolute clearance joints is developed and verified. Then, the influences of different factors on dynamic characteristics of parallel manipulator are explored respectively. This paper contributes to explore the effect of revolute joints clearance on total property of the manipulator. [ABSTRACT FROM AUTHOR]

Interest in the exploration of other planets has led to the success of Ingenuity (Mars helicopter)'s first flight in the Martian atmosphere. Despite this achievement, the flight of aircraft under ultra-low air density, such as Mars, is still limited. A flapping-wing aircraft that mimics nature's flyers can provide an alternative solution to conventional aircraft. Successful flapping flight on Mars, where the air density is very thin, requires an understanding of aerodynamics, and prediction of the dynamic changes of the flapping wing under very-low air density. In this paper, we constructed a simple dynamic model that can predict the changes in aerodynamics and dynamic behavior under various low air densities. The predicted changes were compared with the measured ones in a chamber that could simulate the low air density with a modified flapping-wing system based on our flapping-wing micro-air-vehicle (FW−MAV) models, the KUBeetle. Both prediction and measurement showed that when the air density decreased, the flapping frequency tended to increase due to drag reduction, even without consuming additional power. The model reasonably predicted a large decrease in the lift for the 10 % air density, where the flapping frequency increased by 10 %. Under the 50 % and 25 % low air densities, the measured lift coefficients did not change much. However, under the 10 % air density, the lift coefficient decreased by about 16 % due to less wing rotation and wing twist. While the aerodynamic power was predicted to decrease significantly due to the large decrease in aerodynamic forces under low air density, an increase in the angular velocity and peak angular acceleration caused an increase in the inertial power. Therefore, the amount of reduction in the measured mechanical power consumption under the 10 % air density was relatively small, compared to that under the 100 % air density. This work may provide insights into the design of an FW−MAV for the ultra-thin air density, such as Mars. • The proposed dynamic model reasonably predicted the flapping motion under low air density. • The measured flapping frequency increased by about 15 % under the 10 % air density, consuming about 9 % less power. • The reduction in measured power consumption under low air density was small, due to the large inertial power. • The measured lift coefficient decreased by about 16 % under the 10 % air density, due to less wing Q4 rotation and wing twist. [ABSTRACT FROM AUTHOR]

Accurate predictions concerning a forging process can be obtained by numerical simulation, but only with a thorough knowledge of the main process variables. The material flow behavior and the interface effects are already well studied in the literature, but not the machine behavior, although it is required to estimate blow efficiency and deduce the energy actually transmitted to the workpiece. In this paper, an experimental methodology was applied to determine a spring-mass-damping model and its associated parameters for a screw press. The model and its parameters were identified with press strikes performed without billet. For validation, simulations were performed to predict blows on copper billets. The model's predictions were in good agreement with the experimental measurements for ten consecutive blows on a copper billet. The decrease of process efficiency and the evolution from inelastic blows to elastic blows were correctly depicted by the model. [ABSTRACT FROM AUTHOR]

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background and aims Design, setting and participants Measurements Findings Conclusions Ecological momentary assessment (EMA) studies have previously demonstrated a prospective influence of craving on substance use in the following hours. Conceptualizing substance use as a dynamic system of causal elements could provide valuable insights into the interaction of craving with other symptoms in the process of relapse. The aim of this study was to improve the understanding of these daily life dynamic inter‐relationships by applying dynamic networks analyses to EMA data sets.Secondary analyses were conducted on time‐series data from two 2‐week EMA studies. Data were collected in French outpatient addiction treatment centres. A total of 211 outpatients beginning treatment for alcohol, tobacco, cannabis, stimulants and opiate addiction took part.Using mobile technologies, participants were questioned four times per day relative to substance use, craving, exposure to cues, mood, self‐efficacy and pharmacological addiction treatment use. Multi‐level vector auto‐regression models were used to explore contemporaneous, temporal and between‐subjects networks.Among the 8260 daily evaluations, the temporal network model, which depicts the lagged associations of symptoms within participants, demonstrated a unidirectional association between craving intensity at one time (T0) and primary substance use at the next assessment (T1, r = 0.1), after controlling for the effect of all other variables. A greater self‐efficacy at T0 was associated with fewer cues (r = −0.04), less craving (r = −0.1) and less substance use at T1 (r = −0.07), and craving presented a negative feedback loop with self‐efficacy (r = −0.09).Dynamic network analyses showed that, among outpatients beginning treatment for addiction, high craving, together with low self‐efficacy, appear to predict substance use more strongly than low mood or high exposure to cues. [ABSTRACT FROM AUTHOR]

Educational big data has great predictive power to identify academically at-risk students. Based on fully mining educational big data, this study developed an early alert dynamic model of academically at-risk students to confirm and extend this proposition. An empirical test was carried out to validate the reliability and validity of the dynamic model by using data analysis methods. The results proved that the developed model could precisely identify academically at-risk students, scientifically assess their academic risk status, and dynamically provide personalised interventions. The overall prediction success rate of the developed model was 80.8%. In addition, application reflections were discussed to shed light on future implementation. [ABSTRACT FROM AUTHOR]

Cells store triacylglycerol (TAG) within lipid droplets (LDs). A dynamic model describing complete LD formation at the endoplasmic reticulum (ER) membrane does not yet exist. A biochemical‐biophysical model of LD synthesis is proposed. It describes the time‐dependent accumulation of TAG in the ER membrane as the formation of a potential LD (pLD) bounded by spherical caps of the inner and outer monolayers of the membrane. The expansion rate of the pLD depends on the TAG supply, the elastic properties of the ER membrane, and the recruitment of phospholipids (PLs) to the cap‐covering monolayers. Model simulations provided the following insights: (a) Marginal differences in the surface tension of the cap monolayers are sufficient to fully drive the expansion of the pLD towards the cytosol or lumen. (b) Selective reduction of PL supply to the luminal monolayer ensures stable formation of cytosolic LDs, irrespective of variations in the elasto‐mechanical properties of the ER membrane. (c) The rate of TAG supply to the cytosolic monolayer has a major effect on the size and maturation time of LDs but has no significant effect on the TAG export per individual LD. The recruitment of additional PLs to the cap monolayers of pLDs critically controls the budding direction, size, and maturation time of LDs. The ability of cells to acquire additional LD initiation sites appears to be key to coping with acutely high levels of potentially toxic free fatty acids. [ABSTRACT FROM AUTHOR]

Dynamic models generating time‐dependent model predictions are typically associated with high‐dimensional input spaces and high‐dimensional output spaces, in particular if time is discretized. It is computationally prohibitive to apply traditional global sensitivity analysis (SA) separately on each time output, as is common in the literature on multivariate SA. As an alternative, we propose a novel method for efficient global SA of dynamic models with high‐dimensional inputs by combining a new polynomial chaos expansion (PCE)‐driven partial least squares (PLS) algorithm with the analysis of variance. PLS is used to simultaneously reduce the dimensionality of the input and output variables spaces, by identifying the input and output latent variables that account for most of their joint variability. PCE is incorporated into the PLS algorithm to capture the non‐linear behavior of the physical system. We derive the sensitivity indices associated with each output latent variable, based on which we propose generalized sensitivity indices that synthesize the influence of each input on the variance of entire output time series. All sensitivities can be computed analytically by post‐processing the coefficients of the PLS‐PCE representation. Hence, the computational cost of global SA for dynamic models essentially reduces to the cost for estimating these coefficients. We numerically compare the proposed method with existing methods by several dynamic models with high‐dimensional inputs. The results show that the PLS‐PCE method can obtain accurate sensitivity indices at low computational cost, even for models with strong interaction among the inputs. [ABSTRACT FROM AUTHOR]

Advances in bionic technology have enabled quadruped robots to be more flexible. Numerous quadruped robots in various forms specialize in walking and trotting, whereas very few robots achieve high‐performance obstacle‐overcoming. A bionic quadruped standing long jump obstacle‐overcoming robot is presented. By using two synchronous belts and energy storage, this robot is capable of high‐performance jumping. A flexible spine for the bionic quadruped obstacle‐overcoming robot is also presented to achieve energy storage and shock absorption during obstacle‐overcoming. Furthermore, the control framework by establishing the dynamic models of the single limb is proposed. To validate the feasibility and accuracy of the design theory and robot scheme, simulations are conducted. The results of these simulations clearly illustrate the robot's ability to successfully overcome obstacles of varying heights, thereby affirming the correctness of its limb dynamics models. In comparison to traditional quadruped robots, the bionic quadruped obstacle‐overcoming robot proves its efficacy in navigating challenging terrains. [ABSTRACT FROM AUTHOR]

Highlights In automated fiber placement (AFP), the fiber tension is an important process parameter. Sharp fluctuations in fiber tension are unacceptable in AFP process. The focuses of this article are on fiber tension modeling and control methods for AFP. Firstly, the mechanical model of fiber transport based on frictional loss is established, and the control objective, which should really be focused on in the tension system, is pointed out. Then, identification experiments are carried out to obtain the unknown parameters in the mechanical model. In addition, a dynamic model of fiber tension based on a passive dancer roller is established and linearized by curve fitting. Finally, a variable‐parameter Proportion‐Integration‐Differentiation (PID) controller is established to achieve stable control of the fiber tension. The experimental results show that the proposed control method can accurately stabilize the actual tension at the target value and has a lower control error in the face of strong velocity fluctuations than the traditional tension control system. The fiber tension at the end of the tow transfer path cannot be measured directly by the sensor in automated fiber placement. The tension model predicts the fiber tension at various points in the tow path. The control method using the tension prediction model is much more accurate than the traditional method. [ABSTRACT FROM AUTHOR]

Snake robots have redundant kinematic structure which predetermines them for motion in rough and unstructured terrain with obstacles, narrow spaces or environments with different ground levels. Dynamic modeling of snake robots is an important element in the development of control strategies for them. This paper, deals with the dynamic model of a snake robot moving in a pipeline. The model is based on Newton's mechanics with consideration of the viscous as well as Coulomb friction model. The paper uses Hertz theory for modeling of contact between a snake robot and side walls of a pipeline. Based on optimization process results, the friction effects as well as analyses of snake robot propulsive force are investigated. The main contributions of the paper are the developed dynamic model for snake robot motion in a pipeline, open source code of the developed model in MATLAB, and analyses of individual parameters of snake robot motion. • Propulsive force of snake robot moving in a pipeline is significantly affected by friction of the side walls. • One full sine wave formed by snake robot links ensures maximum average velocity. • Considering Coulomb friction the snake robot performs more jerked motion in comparison with viscous friction. [ABSTRACT FROM AUTHOR]

The engagement quality of a helicopter dry clutch has a significant impact on the service life and overall flight performance of the helicopter. The engagement oil pressure is an important factor affecting the clutch engagement quality. Firstly, a nonlinear input–output dynamic model for the dry clutch is developed to investigate the optimization and control of dry clutch engagement pressure in this paper. Secondly, to efficiently obtain the optimal pressure curve, an optimal method combining the developed dynamic model with the state feedback gain of a linear quadratic optimization regulator (LQR) solver is proposed. Thirdly, considering that hydraulic actuators may struggle with tracking certain pressure curves, a hydraulic actuator for accurately tracking pressure curves based on fuzzy PID is proposed. The simulation results indicate that the developed hydraulic actuator exhibits an excellent tracking performance. Moreover, compared with linear and segmented pressure curves, the optimal pressure curve derived from the proposed method significantly reduces jerk, friction work, and engagement duration, resulting in improved helicopter dry clutch engagement quality. [ABSTRACT FROM AUTHOR]

Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles, heavily reliant on the driving system's performance. While the road wheel is a key component of the driving system, traditional road wheels predominantly adopt a solid structure, exhibiting subpar adhesion performance and damping effects, thereby falling short of meeting the demands for high-speed, stable, and long-distance driving in tracked vehicles. Addressing this issue, this paper proposes a novel type of flexible road wheel (FRW) characterized by a catenary construction. The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic. First, three-dimensional (3D) finite element (FE) models of both flexible and rigid road wheels are established, considering material and contact nonlinearities. These models are validated through a wheel radial loading test. Based on the validated FE model, the paper uncovers the relationship between load and radial deformation of the road wheel, forming the basis for a nonlinear mathematical model. Subsequently, a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law. A random road model, considering the track effect and employing white noise, is constructed. The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades. The results demonstrate that, in comparison to the rigid road wheel (RRW), the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads. This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles. [ABSTRACT FROM AUTHOR]

The purpose of this study is to contribute to the existing body of research on the impact of Corporate Social Responsibility (CSR) on Firm Performance (FP). The study employs a longitudinal panel data sample of 132 automotive companies, using a dynamic Generalized Method of Moments model. The analysis examines the relationship between CSR ratings and yearly financial performance, taking into account various control variables. The results of the analysis suggest that there is a non-linear, U-shaped relationship between CSR and FP. The direction of this relationship (positive or negative) is dependent on the level of CSR engagement. This means that CSR activities do not immediately yield benefits, but instead provide advantages once a certain level of CSR has been reached. The study also finds that the impact of CSR on FP is positively moderated by technological innovation. This indicates that firms with higher levels of investment in technology benefit more from CSR activities in terms of their financial performance. [ABSTRACT FROM AUTHOR]

Research Object: Taking the acquisition mechanism of oscillatory flapping-wing wave energy as the research object, the scheme design and dynamic analysis of the acquisition mechanism are studied. Research Methods: According to the working principle of the acquisition mechanism of oscillatory flapping-wing wave energy, the rotation dynamics model of the acquisition mechanism and the corresponding relationship between the model parameters and the design parameters of the mechanism are established. Based on the momentum moment theorem, the differential equation of the dynamics of the acquisition mechanism and the transfer function of the system are established. The dynamic response of the acquisition mechanism is analyzed, the system parameters are optimized, and the scheme design is carried out. The conversion efficiency of the acquisition mechanism and the energy collection efficiency under different sea conditions are calculated. The motion response of the acquisition mechanism is simulated and analyzed by MATLAB and AQWA software. Research Results: The results show that the response of the crank and swing slider acquisition mechanism is fast and stable, and the average conversion efficiency is 34%. The research process provides an effective reference for the development of the acquisition mechanism of oscillatory flapping-wing wave energy. [ABSTRACT FROM AUTHOR]

Due to the marine environment, the operation efficiency of marine cranes is low, and it is easy to cause safety accidents. In this study, magnetorheological (MR) technology is applied to the field of payload anti-swing for marine crane, and designs a parallel MR anti-swing device. The dynamic model of the anti-swing system is derived based on the robot theory and Lagrange method. To enhance the efficiency of anti-swing and reduce the energy, the variable universe fuzzy PID (VUFPID) controller is designed. The anti-swing effect of MR anti-swing device is simulated and analyzed. The results show that the effect of payload anti-swing is exceed 80%, and the energy consumption of MR anti-swing device with VUFPID controller is reduced by 49% compared with MR anti-swing device with a fixed current (1.9 A) under the approximate anti-swing effect. The physical prototype of MR anti-swing device is installed on the laboratory crane. The experimental results show that the attitude of the payload is reduced by 80%. The proposed MR anti-swing device improve the efficiency of Marine cranes. [ABSTRACT FROM AUTHOR]

Purpose: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID‐19, using data following vaccine availability. Methods: Using electronic health records of patients ≥18 years, with laboratory‐confirmed COVID‐19, from a large care‐delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID‐19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c‐statistic and Brier score. Results: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c‐statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID‐19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c‐statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort. Conclusion: The characteristics of patients hospitalized for COVID‐19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set. [ABSTRACT FROM AUTHOR]

Efficiency of calculating a dynamic response is an important point of the compliant mechanism for posture adjustment. Dynamic modeling with low orders of a 2R1T compliant parallel mechanism is studied in the paper. The mechanism with two out-of-plane rotational and one lifting degrees of freedom (DoFs) plays an important role in posture adjustment. Based on elastic beam theory, the stiffness matrix and mass matrix of the beam element are established where the moment of inertia is considered. To improve solving efficiency, a dynamic model with low orders of the mechanism is established based on a modified modal synthesis method. Firstly, each branch of the RPR type mechanism is divided into a substructure. Subsequently, a set of hypothetical modes of each substructure is obtained based on the C-B method. Finally, dynamic equation of the whole mechanism is established by the substructure assembly. A dynamic experiment is conducted to verify the dynamic characteristics of the compliant mechanism. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate quality of life (QoL) in middle-aged adults living alone and identify comprehensive biological, psychological, interpersonal, and contextual factors related to QoL using the dynamic biopsychosocial model. As a secondary analysis, this study used data from the 2017 Korea Community Health Survey conducted by the Korea Disease Control and Prevention Agency. Methods: Among the total 228,381 respondents, 10,639 middle-aged individuals aged 40–64 years from single-person households (5,036 men and 5,603 women) were included in the analysis. QoL was measured using the EuroQoL-5 Dimension (EQ-5D). The EQ-5D descriptive statistics were provided according to biological, psychological, interpersonal, and contextual factors. Considering the data structure of the multistage stratified cluster sampling method, a complex samples general linear model statistic was used to identify the predictors of QoL. Results: QoL was lower in those who had undesirable psychological status (e.g., more depressive symptoms, poor subjective health, and higher perceived stress), less engagement in social networking (less frequent contact with friends and less frequent participation in social activities such as religious activities, friendship gathering, and leisure), and lower physical, behavioral, and socioeconomic factors. Conclusions: This study's findings indicate that psychological and interpersonal factors should be addressed and prioritized to improve the QoL of middle-aged adults living alone. By providing many opportunities for easily accessible social activities that meet the needs and interests of this demographic, their QoL can be improved through strengthening social support. [ABSTRACT FROM AUTHOR]

In this paper, the vehicle position points obtained by multi-sensor fusion are taken as the observed values, and Kalman filter is combined with the vehicle kinematics equation to further improve the vehicle trajectory. To realize this, mathematical principles of deep reinforcement learning are analyzed, and the theoretical basis of reinforcement learning is also analyzed. It is proved that the controller based on dynamic model is better than the controller based on kinematics in deviation control, and the performance of the controller based on deep reinforcement learning is also verified. The simulation data show that the proportion integration differentiation (PID) controller has a better tracking effect, but it does not have the constraint ability, which leads to radical acceleration change, resulting in unstable acceleration and deceleration control. Therefore, the deep reinforcement learning controller is selected as the longitudinal velocity tracking controller. The effectiveness of lateral and longitudinal motion decoupling strategy is verified by simulation experiments. [ABSTRACT FROM AUTHOR]

Unmanned helicopters are unstable, high-order nonlinear systems. It is difficult to model the system dynamics accurately by physical models due to simplifications and assumptions. Deep learning based modeling methods could achieve high prediction accuracy without any simplifications and assumptions, while their results are hard to interpret. To ensure both accuracy and interpretability, a novel residual hybrid dynamic model is proposed, which combines a physical model, describing the essential dynamic characteristics of unmanned helicopters, and a convolutional neural network and long short-term memory neural network (CNN-LSTM) based deep learning model, compensating the errors of the physical model by the residual connection. Meanwhile, the CNN-LSTM model could efficiently learn the information in both state-control and time dimensions due to the well-designed network structure. Moreover, a two-step optimization method is proposed to optimize parameters of the residual hybrid dynamic model on the flight data from the Stanford Autonomous Helicopter Project. The experiment results demonstrate that the proposed residual hybrid dynamic model exhibits superior accuracy, efficiency, and generalization capabilities compared to the baseline models. [ABSTRACT FROM AUTHOR]

The complex influence of various disturbances on an inertially stabilized platform (ISP) restricts the further improvement of its servo performance. This article investigates the mapping relationship between internal and external disturbances and servo performance by establishing a high-precision dynamics model of the servo device with simulation and experiment. For internal disturbances, a nonlinear model of friction and backlash is established based on a BP neural network, and the transmission error is reconstructed based on the principle of main order invariance. For external disturbances, the road disturbance torque, changing inertia, and mass imbalance torque are modeled. The quantitative mapping relationship between internal and external disturbances and servo performance is obtained through simulation, in which friction and road disturbance are the largest internal and external factors affecting the servo performance, respectively. These conclusions are verified by load simulation experiments on a certain type of servo device, in which the servo performance is improved by 17% for every 25% reduction of friction torque, and the servo performance is reduced by 12% for every 33% increase of road disturbance torque. The research results provide a reference for servo device selection, performance indicator assignment, and performance prediction of the ISP. [ABSTRACT FROM AUTHOR]

The global spread of COVID-19 has profoundly affected health and economies, highlighting the need for precise epidemic trend predictions for effective interventions. In this study, we used infectious disease models to simulate and predict the trajectory of COVID-19. An SEIR (susceptible, exposed, infected, removed) model was established using Wuhan data to reflect the pandemic. We then trained a genetic algorithm-based SEIR (GA-SEIR) model using data from a specific U.S. region and focused on individual susceptibility and infection dynamics. By integrating socio-psychological factors, we achieved a significant enhancement to the GA-SEIR model, leading to the development of an optimized version. This refined GA-SEIR model significantly improved our ability to simulate the spread and control of the epidemic and to effectively track trends. Remarkably, it successfully predicted the resurgence of COVID-19 in mainland China in April 2023, demonstrating its robustness and reliability. The refined GA-SEIR model provides crucial insights for public health authorities, enabling them to design and implement proactive strategies for outbreak containment and mitigation. Its substantial contributions to epidemic modelling and public health planning are invaluable, particularly in managing and controlling respiratory infectious diseases such as COVID-19. [ABSTRACT FROM AUTHOR]

Environmental vibration energy harvesting has received widespread attention recently, but existing research mainly focuses on cantilever beams. The fixing method of the cantilever beams limits its application range. A theoretical model and experimental results of a rectangular piezoelectric beam's modal frequencies and environmental vibration energy harvesting capacity are presented in this study. Accurate evaluation of piezoelectric beams' modal frequencies and energy harvesting capacity is extremely important to monitor and harvest energy from environmental vibrations. This paper establishes a model for the modal frequencies and response of a rectangular piezoelectric beam based on the Euler-Bernoulli beam theory and piezoelectric constitutive equation. In this paper, a fixed-size rectangular piezoelectric beam was selected for verification. The theoretical model was calculated using the modal superposition method. Then, the modal frequencies of piezoelectric beams were simulated using COMSOL, which is a multiphysics simulation software, and compared with theoretical values. Next, the modal frequencies of the piezoelectric beams and the vibration response of the theoretical results were verified through multiple sets of experiments. The experimental results show that the theoretical evaluation error of the modal frequencies of the piezoelectric beams is 1.23%, and the calculation average errors of the output voltage and power of the rectangular piezoelectric beams are 2.7% and 12.3%. The theoretical model effectively predicted the modal frequencies, output voltage, and power of the rectangular piezoelectric beams, demonstrating its potential for monitoring and harvesting environmental vibration energy. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The shallow spall faults will lead to multiple additional contact phenomenon of rolling element passing through the defects in the early stage of crack-to-spall evolution. The existing bearing defect analysis models ignore this stage. In this paper, the mechanism of the shallow spall fault is analyzed, and the width and depth of the spall are quantitatively studied. Based on Hertz contact theory, a multi-impact dynamic model of raceway spall damage on the rolling element bearing outer ring is constructed by time-varying contact displacement and force. The dynamic response of raceway spall damage on the rolling element bearing outer ring is calculated by the Runge–Kutta method under different spall sizes and compared with the existing dual-impact model. The results show that the model accurately describes the phenomenon of weak multi-impact in early stage of the shallow spall. The two-dimensional spall including spall width and depth are quantified in this model, compared with the limitation of the dual-impact model which only quantifies the spall width. This model fills in the blank of the mechanism model with early weak multi-impact characteristics of bearing defect evolution in the whole life. It is of great significance for rolling element bearing damage degree evaluation. [ABSTRACT FROM AUTHOR]

The temperature-varying gap between the full ceramic ball bearings and the steel pedestal in wide temperature ranges leads to misalignment of the bearing rotor system, and there is a significant impact on the vibration of the rotor system. In this paper, the dynamic model considering the temperature-varying gap and time-varying contact between the full ceramic ball bearing and the steel pedestal in wide temperature ranges is proposed. The rigid body elements and the inner rings are coupled in the model, and the influence of the temperature-varying gap is analyzed. Results show that the increased gap at high temperatures brings about the looseness of the full ceramic ball bearing, the misalignment occurs between the axes of the two full ceramic ball bearings due to the looseness. The interaction between the full ceramic ball bearing and the steel pedestal becomes more significant, which causes the vibration of the rotor system to rise. Appropriately increase the interference between the full ceramic ball bearing and the steel pedestal helps reduce the gap at high temperature, thus avoiding the excessive vibration caused by misalignment and improving the rotation accuracy of the rotor system. The research results provide a reference basis for the use of full ceramic ball bearings in wide temperature ranges. [ABSTRACT FROM AUTHOR]

The article is devoted to the study of dynamic processes in the power unit of electric vehicle when shifting gears in a two-shaft gearbox by means of a cone synchronizer. A two-mass dynamic model is used to obtain analytical dependences. This model of the power unit makes it possible to obtain a qualitative idea and a quantitative assessment of the electric vehicle gearshift process, to select parameters of the laws of engine torque and synchronizer friction moment change. For a more precise description of vibrations in a power unit, taking into account its elastic properties, a three-mass dynamic model is considered. An example of calculating the time of shifting from low gear to top one for the MAZ-4381EE delivery electric truck is given. The studies conducted have shown that the vibrational processes occurring in the power unit of electric vehicle do not significantly affect the dynamic loading of its elements.

Abstract Hydrocarbon fuels contain approximately 50 times more energy per unit mass than commercial batteries, thus converting even 10% of the energy contained in hydrocarbon fuels to electrical energy could present a more mass-efficient electrical energy source than batteries. Considering the storability of hydrocarbon fuels compared to hydrogen, the viability of direct hydrocarbon polymer electrolyte membrane fuel cells was examined. With extremely pure (> 99.99%) propane, the cell Open-Circuit Voltage (OCV) was only 0.05 V and produced negligible power. However, with addition of trace quantities of unsaturated hydrocarbons, the cell had an OCV of 0.85 V and produced power, even after the unsaturated hydrocarbon addition was discontinued. At sufficiently high current densities, power output gradually decreased then the cell rapidly “extinguished” but by periodically shutting off the current for short time intervals the average power density could be increased significantly. Chemical analysis revealed that no significant amounts of hydrocarbon intermediates or CO were present in the effluent and that conversion of the hydrocarbon fuel to CO2 and H2O was nearly complete. An analytical model incorporating the relative rates of conversion of active anode catalyst sites to inactive sites and vice versa was developed to interpret this behavior. The model predictions were consistent with the experimental observations; possible physical mechanisms are discussed.

Abstract Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles, heavily reliant on the driving system’s performance. While the road wheel is a key component of the driving system, traditional road wheels predominantly adopt a solid structure, exhibiting subpar adhesion performance and damping effects, thereby falling short of meeting the demands for high-speed, stable, and long-distance driving in tracked vehicles. Addressing this issue, this paper proposes a novel type of flexible road wheel (FRW) characterized by a catenary construction. The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic. First, three-dimensional (3D) finite element (FE) models of both flexible and rigid road wheels are established, considering material and contact nonlinearities. These models are validated through a wheel radial loading test. Based on the validated FE model, the paper uncovers the relationship between load and radial deformation of the road wheel, forming the basis for a nonlinear mathematical model. Subsequently, a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton’s second law. A random road model, considering the track effect and employing white noise, is constructed. The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades. The results demonstrate that, in comparison to the rigid road wheel (RRW), the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads. This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.

Abstract Efficiency of calculating a dynamic response is an important point of the compliant mechanism for posture adjustment. Dynamic modeling with low orders of a 2R1T compliant parallel mechanism is studied in the paper. The mechanism with two out-of-plane rotational and one lifting degrees of freedom (DoFs) plays an important role in posture adjustment. Based on elastic beam theory, the stiffness matrix and mass matrix of the beam element are established where the moment of inertia is considered. To improve solving efficiency, a dynamic model with low orders of the mechanism is established based on a modified modal synthesis method. Firstly, each branch of the RPR type mechanism is divided into a substructure. Subsequently, a set of hypothetical modes of each substructure is obtained based on the C-B method. Finally, dynamic equation of the whole mechanism is established by the substructure assembly. A dynamic experiment is conducted to verify the dynamic characteristics of the compliant mechanism.

Abstract Background This study aimed to investigate quality of life (QoL) in middle-aged adults living alone and identify comprehensive biological, psychological, interpersonal, and contextual factors related to QoL using the dynamic biopsychosocial model. As a secondary analysis, this study used data from the 2017 Korea Community Health Survey conducted by the Korea Disease Control and Prevention Agency. Methods Among the total 228,381 respondents, 10,639 middle-aged individuals aged 40–64 years from single-person households (5,036 men and 5,603 women) were included in the analysis. QoL was measured using the EuroQoL-5 Dimension (EQ-5D). The EQ-5D descriptive statistics were provided according to biological, psychological, interpersonal, and contextual factors. Considering the data structure of the multistage stratified cluster sampling method, a complex samples general linear model statistic was used to identify the predictors of QoL. Results QoL was lower in those who had undesirable psychological status (e.g., more depressive symptoms, poor subjective health, and higher perceived stress), less engagement in social networking (less frequent contact with friends and less frequent participation in social activities such as religious activities, friendship gathering, and leisure), and lower physical, behavioral, and socioeconomic factors. Conclusions This study’s findings indicate that psychological and interpersonal factors should be addressed and prioritized to improve the QoL of middle-aged adults living alone. By providing many opportunities for easily accessible social activities that meet the needs and interests of this demographic, their QoL can be improved through strengthening social support.

Abstract The global spread of COVID-19 has profoundly affected health and economies, highlighting the need for precise epidemic trend predictions for effective interventions. In this study, we used infectious disease models to simulate and predict the trajectory of COVID-19. An SEIR (susceptible, exposed, infected, removed) model was established using Wuhan data to reflect the pandemic. We then trained a genetic algorithm-based SEIR (GA-SEIR) model using data from a specific U.S. region and focused on individual susceptibility and infection dynamics. By integrating socio-psychological factors, we achieved a significant enhancement to the GA-SEIR model, leading to the development of an optimized version. This refined GA-SEIR model significantly improved our ability to simulate the spread and control of the epidemic and to effectively track trends. Remarkably, it successfully predicted the resurgence of COVID-19 in mainland China in April 2023, demonstrating its robustness and reliability. The refined GA-SEIR model provides crucial insights for public health authorities, enabling them to design and implement proactive strategies for outbreak containment and mitigation. Its substantial contributions to epidemic modelling and public health planning are invaluable, particularly in managing and controlling respiratory infectious diseases such as COVID-19.

ABSTRACTEveryone has a different level of interest in a trending topic posted on social media, which may affect user’s behaviour. In order to find out the way it affects the process of information transmission, we construct an interest intensity-based susceptible-forwarding-immune[Formula: see text] propagation dynamic model and two parameters birth rate[Formula: see text] and death rate[Formula: see text] are introduced to represent the users who newly join the group of disseminated information and the users who leave this population. And we give different birth rates to people with various levels of interest, which helps us to determine the interest intensity of potential users to a certain extent. We use the forwarding data of the real topic on Chinese Sina-microblog for data fitting, which can accurately parameterize the model and quantify the impact of interest intensity. And sensitivity analyses also give some strategies for increasing the impact of information dissemination process from the perspective of interest intensity.