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Background Cardiovascular disease is the primary cause of death and Disease burden of Chinese residents, and the situation of prevention and control is grim. Management of risk factors for cardiovascular disease is an important foundation for preventing cardiovascular disease. However, there is currently limited research on the influencing risk factors of cardiovascular disease risk in elderly patients with chronic disease in primary care using single lead wearable electrocardiogram devices both domestically and internationally, and previous studies have not ranked the importance of variables containing different quantities of risk in patients from a holistic perspective. Objective The aim of this study is to analyze the influencing factors of the comprehensive risk of cardiovascular disease in elderly patients with chronic disease aged 65 and above in primary care in Ningxia, and to provide objective basis and assistance for the comprehensive prevention and control of cardiovascular disease in primary care. Methods From December 2021 to September 2022, totally 3 039 patients over 65 years old with hypertension, diabetes and coronary heart disease, including at least one chronic disease, from 26 primary care health center in Ningxia were selected as the research subjects. According to the analysis of the 72 hour electrocardiogram, there were 632 cases in the normal group and 2 407 cases in the risk group. Analyze the basic information of two groups of patients to determine the best λ Value, draw a model, and use LASSO regression and multivariate Logistic regression to analyze the comprehensive risk factors of cardiovascular disease in elderly patients with chronic diseases; and rank the variables that affect the overall risk of cardiovascular disease and include different numbers of risks among patients. Results The differences in age, gender, BMI, education level, occupation, urban-rural distribution, smoking, exercise, coronary heart disease combined with diabetes, hypertension combined with coronary heart disease and diabetes between the two groups of patients were statistically significant (P

AlCoCrFeNi2.1 eutectic high-entropy alloy is characterized by a fine, homogeneous, and regular lamellar structure, as well as good organizational structure and mechanical properties with both strength and plasticity over a wide range of temperature (70-1000 K) and compositional deviation, thus making it the most widely studied eutectic high-entropy alloy at present. In this paper, regarding the additive manufacturing of AlCoCrFeNi2.1 eutectic high-entropy alloy, the influence of different processes and process parameters on the microstructure and mechanical properties of the alloy was reviewed, and the phase distribution, microstructure, and strengthening mechanism of AlCoCrFeNi2.1 eutectic high-entropy alloy prepared by the selective laser melting technology were highlighted. Finally, it points out the differences and deficiencies in phase formation mechanism and organization evolution process of the current additive manufacturing AlCoCrFeNi2.1 eutectic high-entropy alloy and puts forward the development direction of material modification of AlCoCrFeNi2.1 eutectic high-entropy alloy as the substrate of the material modification and the new technology of additive manufacturing high-entropy alloy, which will provide ideas for the promotion of the industrialized application of the alloy.

The traditional freeway safety studies with 'poststatic' thinking basically use cross-sectional data or panel data, which find it difficult to figure out real-time traffic crash risk factors. With the development of information collection technology, it is possible to obtain high-resolution traffic flow data currently, which provide a data basis for the dynamic traffic safety research towards freeways. This research aims at accurately identifying the real-time traffic crash precursors on freeways and addressing the shortcomings of conventional dynamic traffic safety research with the thinking of limited factor dimensions. In this research, dimensional data were applied as input model variables, the input dataset includes traffic crash data and the matched dynamic traffic flow data, and weather information and road characteristics were also considered to figure out the interaction effects between these dimensional factors. The XGBoost (eXtreme Gradient Boosting) was carried out to identify the dynamic crash-prone variables and the SHAP (SHapley Additive exPlanations) interpreter was introduced to interpret the XGBoost model, as well as the visualization of the influence of each eigenvalue on the traffic crash was realized. The results indicate that, in addition to traffic flow variables, road, weather, and temporal characteristics also have an impact on the traffic crash risk, and there is an interaction between each feature. The results of this research can provide the theoretical basis for freeway real-time traffic crash prediction and safety control., Author(s): Jie Li [1,2]; Yang Yang (corresponding author) [3,4]; Yanran Hu [5]; Xinyuan Zhu [1,6]; Naixuan Ma [1,6]; Xiaojing Yuan [5] 1. Introduction Over the past decades, road traffic safety [...]

A spatial redundantly actuated parallel mechanism (RAPM) constrained by two point contact higher kinematic pairs (HKPs) has been designed, arising from the inspiration of mastication in human beings: the end effector is the lower jaw, the six kinematic chains are the primary chewing muscles, and the constraints at HKPs are the temporomandibular joints. In this paper, firstly, the constrained motions of the mechanism are described in detail; thereafter, five models are formulated by the well-known Newton–Euler's law, the Lagrangian equations, and the principle of virtual work, to explore its rigid-body inverse dynamics. The symbolic results show that the model structures based on these approaches are quite different: the model via the Newton–Euler law well reflects the nature of the mechanism in terms of the constraint forces from HKPs with six equations and eight unknowns, and the existence of reaction forces at the spherical joints is tightly dependent on the number of kinematic chains. In comparison, from the latter two methods, the constraint forces and the reaction forces at spherical joints do not appear in the four models in which there are only four equations and six unknowns. Further, by using the dynamics model of the non-redundantly actuated counterpart as the core in both the second models from the energy and virtual work-related methods, their computational cost is only about 16.7% and 36.63% of the two first models, respectively. Finally, the comparisons between the dynamics models of the RAPM and its counterpart clarify that the HKP constraints greatly alter the model structures and raise the technical difficulties. [ABSTRACT FROM AUTHOR]

This paper presents a comparative study of the rigid-body inverse dynamics of a spatial redundantly actuated parallel mechanism constrained by two point contact higher kinematic pairs (HKPs). Firstly, its constrained motions are analysed comprehensively, then four different models are formulated by the generalized momentum approach and the Lagrange-D'Alembert formulation to explore its inverse dynamics. In each method, the first model is built by employing the method directly to the mechanism. In the second model, the dynamic model of its non-redundantly actuated counterpart free of HKPs is built by this approach first, then the constraints from HKPs are modelled, to finally reach the model of the redundantly actuated parallel mechanism (RAPM) where that of its counterpart is utilised as the core. The four models give rise to equivalent numerical results, and the second model in both methods of the RAPM can alleviate the strong coupling between the parasitic motion variables and degrees of freedom (DOFs), boosting the computational speed as fast as that of its non-redundantly actuated counterpart without simplification or loss of accuracy. The comparisons between the mechanism and its counterpart validate that the HKP constraints greatly increase the computational complexity, and the torques required by the parasitic motions of the end effector are significantly smaller than those by the corresponding DOFs.

In this paper, a bio-inspired masticatory mechanism has been developed to reproduce the chewing behaviors of human beings. It is a natural spatial parallel mechanism constrained directly by the base at its end effector. These constraints form two point-contact higher kinematic pairs, producing parasitic motions and redundant actuations simultaneously. To facilitate the model-based control, a rigid-body inverse dynamic model is built and the inertia coupling is analyzed. Firstly, by virtue of a dynamic method, the Hessian matrices of the constraint equations and the kinetic energy are derived. The modeling process is straightforward, and the correctness is validated by virtue of the classical Lagrange equations. However, from the comparison between the technique in this method and a classical method in computing the first time derivative of the Jacobian matrices and the Coriolis–centrifugal force matrix, the former is more time-consuming. Secondly, the inertia coupling is analyzed via the inertia matrix in the joint space, showing that the first, third, and fourth active joints are the most strongly coupled. Finally, by comparing both the inverse dynamics and inertia coupling of the target mechanism and its counterpart, the foregoing constraints raise the computational cost of the inverse dynamics extraordinarily but greatly alleviate the inertia coupling. [ABSTRACT FROM AUTHOR]