The construction of one-dimensional Daubechies wavelet-based finite elements for structural response analysis

The objective of this paper is to develop a family of wavelet-based finite elements for structural response analysis. First, independent wavelet bases are used to approximate displacement functions, unknown coefficients are determined through imposing the continuity, linear independence, completeness, and essential boundary conditions. A family of Daubechies wavelet-based shape functions are then developed, which are hierarchical due to multiresolution property of wavelet. Secondly, to construct wavelet-based finite elements, derivation of the shape functions for a subdomain is employed. Thus, the wavelet-based finite elements being presented are embodied with properties in adaptivity as well as locality. By wavelet preconditioning technology, the two difficulties involving imposition of boundary conditions and compatibility with the traditional finite element methods, which are gathered in the experiments of wavelet-Galerkin context, are well overcome. Numerical examples are used to illustrate the characteristics of the current elements and to assess their accuracy and efficiency

A joint stiffness identification method based on finite element modeling and frequency response functions

Accurate finite element (FE) modeling of mechanical structures is extremely difficult with unknown joints or boundary conditions. An alternative joint stiffness identification method that involves a hybrid of FE model and frequency response functions (FRFs) is presented. Firstly, the joint stiffness is assumed by experience and the mechanical structure is modeled with the FE method. Secondly, the FRFs at the concerned nodes of the structure are simulated and measured, respectively. Then the norm of residual FRFs between the simulations and measurements is calculated. Finally, a sensitivity-based iterative algorithm is derived for minimizing the norm of residual FRFs and the least square method is used to solve over-determined iterative equation. The joints stiffness parameters are identified through the iteration process, while the FE model is updated simultaneously. The proposed joint stiffness identification method is applied on a clamped beam assembly. The first three natural frequencies calculated by the FE model are compared with the measured values. The largest relative error of the simulation deceases from 16.7 % to 2.5 % after the joint stiffness parameters are identified, which demonstrates the effectiveness of the presented method

The multivariable finite elements based on B-spline wavelet on the interval for 1D structural mechanics

Wavelet finite elements with two kinds of variables for 1D structural mechanics are constructed based on B-spline wavelet on the interval (BSWI) and the generalized variational principle. In contrast to the traditional method, the BSWI element with two kinds of variables (TBSWI) can improve the solution accuracy of the generalized stress apparently, because generalized displacement and stress are interpolated separately. Another superiority of the elements constructed is the interpolating function BSWI, which has very good approximation property, further guarantees solution accuracy. Euler beam, Timoshenko beam and Elastic foundation beam are studied providing several numerical examples to verify the efficiency

Study of characteristic variations of high-speed spindles induced by centrifugal expansion deformations

High-speed machining has continuously pushed the demand of spindles with higher speed and higher reliability. In order to design, analyze, and test spindles in a virtual environment, accurate modeling of the spindle dynamics during the running state is essential. This paper investigates the variations of interference fit and bearing preload condition induced by centrifugal expansion deformations at high speed. Firstly, the elastic expansion deformations of the rotating parts due to centrifugal force are calculated based on mechanics of elasticity. It is found that the centrifugal expansion deformation of the bearing inner ring is much larger than the deformation of the shaft when the rotational speed increases, and therefore the amount of the interference between the shaft and the bearing decreases with the speed. Then, with consideration of the centrifugal expansion deformation, a dynamic model of high-speed rolling ball bearings is presented with experimental validation. With the proposed bearing model, centrifugal effects on the bearing preload condition are studied in detail. It is shown that the bearing contact angle decreases, while the contact load increases with the centrifugal expansion deformation of the bearing inner ring. The radial bearing stiffness increases, whereas the axial bearing stiffness decreases a little, due to the resultant effects of the decreased contact angle and the increased contact load. The preload condition of the spindle bearing is strengthened by the centrifugal expansion effect of the bearing inner ring

A spring dashpot model for dynamic analysis of beam-like structure with clearance

In a large number of engineering structures, clearance always exists due to assemblage, manufacturing errors and wear. The presence of clearance may lead to intermittent contact or impacts. For such structures accurate assessment of dynamic response is necessary for design against excessive vibration and wear as well as noise. In this paper we are interested in the study of the dynamic behavior of a cantilever beam structure with clearance. Simulation and experimental tests were carried out for this goal. For simulation tests, clearance was equivalent to a spring-dashpot model with consideration of vertical and angular motions, the impact of beam and boundary face was also taken into consideration. A cantilever beam set-up was designed and built for experimental validations. The presented results showed that the system responses were greatly influenced in the presence of clearance. The peak value of beam’s time-domain signal is larger with the clearance enlargement. The high-order harmonics are more possible to exist in frequency-domain signals when clearance size increases. The effects of clearance should not be ignored when analyzing the dynamic performance and vibration characteristic of engineering structures

HOFA: Twitter Bot Detection with Homophily-Oriented Augmentation and Frequency Adaptive Attention

Twitter bot detection has become an increasingly important and challenging task to combat online misinformation, facilitate social content moderation, and safeguard the integrity of social platforms. Though existing graph-based Twitter bot detection methods achieved state-of-the-art performance, they are all based on the homophily assumption, which assumes users with the same label are more likely to be connected, making it easy for Twitter bots to disguise themselves by following a large number of genuine users. To address this issue, we proposed HOFA, a novel graph-based Twitter bot detection framework that combats the heterophilous disguise challenge with a homophily-oriented graph augmentation module (Homo-Aug) and a frequency adaptive attention module (FaAt). Specifically, the Homo-Aug extracts user representations and computes a k-NN graph using an MLP and improves Twitter's homophily by injecting the k-NN graph. For the FaAt, we propose an attention mechanism that adaptively serves as a low-pass filter along a homophilic edge and a high-pass filter along a heterophilic edge, preventing user features from being over-smoothed by their neighborhood. We also introduce a weight guidance loss to guide the frequency adaptive attention module. Our experiments demonstrate that HOFA achieves state-of-the-art performance on three widely-acknowledged Twitter bot detection benchmarks, which significantly outperforms vanilla graph-based bot detection techniques and strong heterophilic baselines. Furthermore, extensive studies confirm the effectiveness of our Homo-Aug and FaAt module, and HOFA's ability to demystify the heterophilous disguise challenge.Comment: 11 pages, 7 figure

Elucidation of Relaxation Dynamics Beyond Equilibrium Through AI-informed X-ray Photon Correlation Spectroscopy

Understanding and interpreting dynamics of functional materials \textit{in situ} is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales, however spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work we have developed an unsupervised deep learning (DL) framework for automated classification and interpretation of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system behavior. We demonstrate how this method can be used to rapidly explore large datasets to identify samples of interest, and we apply this approach to directly correlate bulk properties of a model system to microscopic dynamics. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery

Health-seeking behavior and barriers to treatment of patients with upper gastrointestinal cancer detected by screening in rural China: real-world evidence from the ESECC trial.

BACKGROUND: To fully realize efficacy in cancer screening, timely and appropriate treatment for participants with malignant lesions is critical. However, the health-seeking behavior of patients with upper gastrointestinal (G.I.) cancer identified in population-level screening programs in China is unknown. METHODS: A community-based real-world investigation was conducted with 136 upper G.I. cancer patients detected in a large screening cohort in an area of high-risk for upper G.I. cancer in China. Using local medical claims data and semi-structured face-to-face interview, we collected information regarding the clinical treatment regimen and factors which result in the lack of timely and appropriate treatment. FINDINGS: The treatment records for 133 upper G.I. cancer patients were acquired. Among these, 48 (36•09%) patients did not receive treatment within three months of initial diagnosis, and treatment of early-stage cancer was more likely to be delayed. Sixteen patients did not seek further diagnostic testing due to their low health-awareness and socio-economic status. Another 20 participants proactively sought further diagnostic evaluation in health care facilities but were prevented from receiving further treatment due to low sensitivity of given diagnostic test(s), failure to recognize the significance of screening results, and/or lack of basic knowledge of diagnosis and treatment for early cancer on the part of clinicians. The treatment regimen offered to patients depended largely on the level of health care facilities they visited, and non-medical factors were the main reasons for choice of health care facilities. INTERPRETATION: A coordinated, system-based management strategy is urgently needed to support the design of upper G.I. cancer screening programs in rural populations in China. FUNDING: The Charity Project of the National Ministry of Health (201202014), the National Key R & D Program of China (2016YFC0901404), the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), and the National Natural Science Foundation of China (82073626)

Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China.

BACKGROUND: We aimed to establish a Medical-Insurance-System-based Cancer Surveillance System (MIS-CASS) in China and evaluate the completeness and timeliness of this system through reporting cancer incidence rates using claims data in two regions in northern and southern China. METHODS: We extracted claims data from medical insurance systems in Hua County of Henan Province, and Shantou City in Guangdong Province in China from Jan 1, 2012 to Jun 30, 2019. These two regions have been considered to be high risk regions for oesophageal cancer. We developed a rigorous procedure to establish the MIS-CASS, which includes data extraction, cleaning, processing, case ascertainment, privacy protection, etc. Text-based diagnosis in conjunction with ICD-10 codes were used to determine cancer diagnosis. FINDINGS: In 2018, the overall age-standardised (Segi population) incidence rates (ASR World) of cancer in Hua County and Shantou City were 167·39/100,000 and 159·78/100,000 respectively. In both of these areas, lung cancer and breast cancer were the most common cancers in males and females respectively. Hua County is a high-risk region for oesophageal cancer (ASR World: 25·95/100,000), whereas Shantou City is not a high-risk region for oesophageal cancer (ASR World: 11·43/100,000). However, Nanao island had the highest incidence of oesophageal cancer among all districts and counties in Shantou (ASR World: 36·39/100,000). The age-standardised male-to-female ratio for oesophageal cancer was lower in Hua County than in Shantou (1·69 vs. 4·02). A six-month lag time was needed to report these cancer incidences for the MIS-CASS. INTERPRETATION: MIS-CASS efficiently reflects cancer burden in real-time, and has the potential to provide insight for improvement of cancer surveillance in China. FUNDING: The National Key R&D Program of China (2016YFC0901404), the Digestive Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals (XXZ0204), the Sanming Project of Shenzhen (SZSM201612061), and the Shantou Science and Technology Bureau (190829105556145, 180918114960704)