Vibration characteristics analysis of mistuned bladed disk system based on mobile interface prestressed CMS super-element method

A new mobile interface prestressed component mode synthesis (CMS) super-element method is proposed with the mobile interface prestressed and free interface super-element approach. Analysis accuracy of this method is verified by the cyclic symmetry analysis method and the direct method. The mistuning parameter of real blades is identified by modal testing and finite element method, and the vibration characteristics of the real mistuned bladed disk system are analyzed based on the mobile interface CMS method. The results showed that the maximum relative error of the dynamic frequency of tuned and mistuned examples are 0.0043 % and 0.1466 %, respectively, which can be to meet the requirement of analytical precision. Compared with the cyclic symmetry analysis method, direct method and fixed interface prestressed CMS super-element method, this method is more suitable for analyzing the vibration characteristics of arbitrary mistuned bladed disk system

MedChatZH: a Better Medical Adviser Learns from Better Instructions

Generative large language models (LLMs) have shown great success in various applications, including question-answering (QA) and dialogue systems. However, in specialized domains like traditional Chinese medical QA, these models may perform unsatisfactorily without fine-tuning on domain-specific datasets. To address this, we introduce MedChatZH, a dialogue model designed specifically for traditional Chinese medical QA. Our model is pre-trained on Chinese traditional medical books and fine-tuned with a carefully curated medical instruction dataset. It outperforms several solid baselines on a real-world medical dialogue dataset. We release our model, code, and dataset on https://github.com/tyang816/MedChatZH to facilitate further research in the domain of traditional Chinese medicine and LLMs.Comment: 7 pages, 3 figure

An analytical investigation on the dynamic stability of a rotor filled with liquid

This paper deals with the dynamic stability of a rigid rotor arbitrarily filled with liquid. On the basis of the established coupled-field equations of the rotor system, the general whirling eigenequation, which is a quartic complex coefficients equation, is derived. In order to obtain the solutions of the general whirling eigenequation, a mathematical method is proposed. To illustrate the precision of calculating results, a comparison is carried out between the present analysis and the numerical results. The results show that two calculation results are in good agreement. Then the stability of the rotor system is analyzed. It is shown that the dynamic instability occurs at a particular bound of the spinning speed. Moreover, the effects of system parameters, such as fluid-fill ratio and mass ratio, on the unstable regions are discussed

Vibration Analysis of Aeroengine Blisk Structure Based on a Prestressed CMS Super-Element Method

For vibration analysis of aeroengine blisk structure, a prestressed component modal synthesis (CMS) super-element method is put forward with the fixed interface prestressing and free interface super-element approach. Based on this method, natural vibration characteristics of blisk structure are calculated at different modal truncation numbers. Comparing with the accurate result of global method, the selection principle of modal truncation number is obtained which affects the accuracy of prestressed CMS super-element method. Vibration response of two-stage blisk structure is calculated by this method, and the effects of different blade aspect ratios have been discussed on vibration characteristics. The results show that prestressed CMS super-element method is in the high accuracy and efficiency on blisk vibration analysis. Resonant frequencies in vibration response are nearly the same between the first-stage blisk and the second-stage blisk, and they are both approximately located in the range 588 Hz–599 Hz. The maximum displacement and dynamic stress are at blade tip and root of the first-stage blisk, respectively. Blade aspect ratio is a key factor of blisk vibration; the effects of blade aspect ratio on natural frequencies are different in the conditions of fixed width and fixed length. This research provides the theoretical basis for dynamic design of aeroengine compressor rotor system

The potential of the Medical Digital Twin in diabetes management: a review

Diabetes is a chronic prevalent disease that must be managed to improve the patient's quality of life. However, the limited healthcare management resources compared to the large diabetes mellitus (DM) population are an obstacle that needs modern information technology to improve. Digital twin (DT) is a relatively new approach that has emerged as a viable tool in several sectors of healthcare, and there have been some publications on DT in disease management. The systematic summary of the use of DTs and its potential applications in DM is less reported. In this review, we summarized the key techniques of DTs, proposed the potentials of DTs in DM management from different aspects, and discussed the concerns of this novel technique in DM management

PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications

Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Compared to natural language models, protein amino acid sequences have a smaller data volume and a limited combinatorial space. Choosing an appropriate vocabulary size to optimize the pre-trained model is a pivotal issue. Moreover, despite the wealth of benchmarks and studies in the natural language community, there remains a lack of a comprehensive benchmark for systematically evaluating protein language model quality. Given these challenges, PETA trained language models with 14 different vocabulary sizes under three tokenization methods. It conducted thousands of tests on 33 diverse downstream datasets to assess the models' transfer learning capabilities, incorporating two classification heads and three random seeds to mitigate potential biases. Extensive experiments indicate that vocabulary sizes between 50 and 200 optimize the model, whereas sizes exceeding 800 detrimentally affect the model's representational performance. Our code, model weights and datasets are available at https://github.com/ginnm/ProteinPretraining.Comment: 46 pages, 4figures, 9 table

Iterative response surface joint algorithm analysis of optimization arrangement on mistuned blades

This paper presents a test method to measure vibration characteristics of mistuned bladed disk system. Modal analysis for the disk is to verify the precision of test bench. Further mistuned parameter identification method is proposed to introduce stiffness detuning. From this the samples can be obtained. On the other hand, the joint optimization analysis system is applied which consists of iterative response surface method and particle swarm optimization algorithm. At the same time, it is proved to have higher accuracy and better generalization ability than standard polynomial response surface method for the problem in this paper. The research results indicate that the amplitudes of optimal solution are smaller than that with random arrangement. The vibration response can be improved obviously, especially for resonance region. So, this paper has a certain universality and application value for blade arrangement based on iterative response surface joint algorithm

Discovering medication patterns for high-complexity drug-using diseases through electronic medical records

An Electronic Medical Record (EMR) is a professional document that contains all data generated during the treatment process. The EMR can utilize various data formats, such as numerical data, text, and images. Mining the information and knowledge hidden in the huge amount of EMR data is an essential requirement for clinical decision support, such as clinical pathway formulation and evidence-based medical research. In this paper, we propose a machine-learning-based framework to mine the hidden medication patterns in EMR text. The framework systematically integrates the Jaccard similarity evaluation, spectral clustering, the modified Latent Dirichlet Allocation and cross-matching among multiple features to find the residuals that describe additional knowledge and clusters hidden in multiple perspectives of highly complex medication patterns. These methods work together, step by step to reveal the underlying medication pattern. We evaluated the method by using real data from EMR text (patients with cirrhotic ascites) from a large hospital in China. The proposed framework outperforms other approaches for medication pattern discovery, especially for this disease with subtle medication treatment variances. The results also revealed little overlap among the discovered patterns; thus, the distinct features of each pattern are well studied through the proposed framework

Doped Titanium Dioxide Films Prepared by Pulsed Laser Deposition Method

TiO2 was intensively researched especially for photocatalystic applications. The nitrogen-doped TiO2 films prepared by pulsed laser deposition (PLD) method were reviewed, and some recent new experimental results were also presented in this paper. A new optical transmission method for evaluating the photocatalystic activity was presented. The main results are (1) PLD method is versatile for preparing oxide material or complex component films with excellent controllability and high reproducibility. (2) Anatase nitrogen-doped TiO2 films were prepared at room temperature, 200°C, and 400°C by PLD method using novel ceramic target of mixture of TiN and TiO2. UV/Vis spectra, AFM, Raman spectra, and photocatalystic activity for decomposition of methyl orange (MO) tests showed that visible light response was improved at higher temperature. (3) The automatic, continuous optical transmission autorecorder method is suitable for detecting the photodecomposition dynamic process of organic compound

Characterization of Bovine Induced Pluripotent Stem Cells by Lentiviral Transduction of Reprogramming Factor Fusion Proteins

Pluripotent stem cells from domesticated animals have potential applications in transgenic breeding. Here, we describe induced pluripotent stem (iPS) cells derived from bovine fetal fibroblasts by lentiviral transduction of Oct4, Sox2, Klf4 and c-Myc defined-factor fusion proteins. Bovine iPS cells showed typical colony morphology, normal karyotypes, stained positively for alkaline phosphatase (AP) and expressed Oct4, Nanog and SSEA1. The CpG in the promoter regions of Oct4 and Nanog were highly unmethylated in bovine iPS cells compared to the fibroblasts. The cells were able to differentiate into cell types of all three germ layers in vitro and in vivo. In addition, these cells were induced into female germ cells under defined culture conditions and expressed early and late female germ cell-specific genes Vasa, Dazl, Gdf9, Nobox, Zp2, and Zp3. Our data suggest that bovine iPS cells were generated from bovine fetal fibroblasts with defined-factor fusion proteins mediated by lentivirus and have potential applications in bovine transgenic breeding and gene-modified animals