Experimental investigations and field applications of a tension estimation method for two linked suspenders using only local vibration measurements by Wen-Hwa Wu, Chien-Chou Chen, Meng-Xuan Wu, Gwolong Lai

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Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening by Lizi Li, Puchen Zhao, Can Yang, Qin Yin, Na Wang, Yan Liu, Yanfang Li

“…Notably, Rotigotine, a marketed drug, was newly recognized for its anti-AD potential, with further enzyme kinetic analyses revealing that it acts as a mixed-type inhibitor in a non-competitive mode. Fluorescence spectroscopy, molecular docking, and molecular dynamics simulations further clarified their binding modes and stability. …”
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LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens by Alexander Wolfertz, Alex Gustschin, Michael Schulz, Alexander M. Long, Anton Khaplanov, Tsviki Y. Hirsh, Andrei Nomerotski, Manuel Morgano, Anton Tremsin, Giacomo Mauri, G. Jeff Sykora, Adrian Losko

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GIS vibration signal denoising algorithm based on SVD-IACMD by TU Jiayi, GUAN Xiangyu, ZHAO Junyi, LIN Jiangang, LAI Zekai

“…In response to the current situation, an on-site vibration signal denoising diagnosis algorithm based on the singular value decomposition (SVD)-improve adaptive chirp mode decomposition (IACMD) algorithm is proposed. …”
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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

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Development of a novel sustainable, portable, fast, and non-invasive platform based on ATR-FTIR technology coupled with machine learning algorithms for Helicobacter pylori detectio... by Ghabriel Honório-Silva, Marco Guevara-Vega, Nagela Bernadelli Sousa Silva, Marcelo Augusto Garcia-Júnior, Deborah Cristina Teixeira Alves, Luiz Ricardo Goulart, Mario Machado Martins, André Luiz Oliveira, Rui Miguel Pinheiro Vitorino, Thulio Marquez Cunha, Carlos Henrique Gomes Martins, Murillo Guimarães Carneiro, Robinson Sabino-Silva

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Research on Bearing Fault Diagnosis Method Based on MESO-TCN by Ruibin Gao, Jing Zhu, Yifan Wu, Kaiwen Xiao, Yang Shen

“…Specifically, ensemble empirical mode decomposition (EEMD) is combined with a hybrid entropy criterion to preprocess the raw vibration signals and suppress redundant noise. …”
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The Effect of Extended Smartphone Screen Time on Continuous Partial Attention by M. Fırat

“…Students attributed this finding to hypnotic algorithms, distracting redundancy, marketing and advertising, passive receiver mode, short video flow, and surprising content. …”
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Bearing Fault Diagnosis Based on Parameter Optimized VMD and ELM with Improved SSA by Yang Sen, Wang Hengdi, Cui Yongcun, Li Chang, Tang Yuanchao

“…Finally, through the screening of coefficients of the variation method, the root mean square value and peak value are constructed as the two-dimensional eigenvalue vector of the first layer, and the sample entropy, kurtosis and root mean square are constructed as the three-dimensional eigenvalue vector of the second layer, which are respectively sent to the limit learning machine ELM for the training and classification of rolling bearing faults.The experiment results show that the proposed algorithm has good fault diagnosis performance,ultimately achieving a classification accuracy of 98.25% and an actual diagnostic accuracy of 93.36%.…”
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A Multi-Mode Recognition Method for Broadband Oscillation Based on Compressed Sensing and EEMD by Jinggeng Gao, Honglei Xu, Yong Yang, Haoming Niu, Jinping Liang, Haiying Dong

“…Finally, we use the EEMD algorithm to decompose the reconstructed signal; the intrinsic mode function (IMF) components containing wideband oscillation information are screened by the energy coefficient, and the wideband oscillation information is identified.…”
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High throughput computational screening and interpretable machine learning for iodine capture of metal-organic frameworks by Haoyi Tan, Yukun Teng, Guangcun Shan

“…In addition to 6 structural features, 25 molecular features (encompassing the types of metal and ligand atoms as well as bonding modes) and 8 chemical features (including heat of adsorption and Henry’s coefficient) were incorporated to enhance the prediction accuracy of the machine learning algorithms. …”
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Alpha-Fetoprotein Detection of Hepatocellular Carcinoma Leads to a Standardized Analysis of Dynamic AFP to Improve Screening Based Detection. by Thomas G Bird, Polyxeni Dimitropoulou, Rebecca M Turner, Sara J Jenks, Pearce Cusack, Shiying Hey, Andrew Blunsum, Sarah Kelly, Catharine Sturgeon, Peter C Hayes, Sheila M Bird

“…An algorithm was devised in static mode, then tested dynamically. …”
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Diagnosis of bipolar disorder based on extracted significant biomarkers using bioinformatics and machine learning algorithms by Hamid Mohseni, Massoud Sokouti, Akram Nezhadi, Ali Sayadi

“…One model was developed using artificial neural network and tanh functions and the other model was developed using decision tree algorithm. Practical Implications. The model developed by artificial neural network and the decision tree can be used in the diagnosis of bipolar disorder in order to screen conscripts who have this disorder with a high risk of relapse and exacerbation of symptoms.…”
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A monthly runoff prediction model based on ICEEMD-L-SHADE-SRU by Ziyang Kou, Yang Yang, Zhiping Li, Xiaoshuang Fu

“…Taking the runoff data from three hydrological stations in the lower reaches of the Yellow River as an example, an improved complementary ensemble empirical mode decomposition (ICEEMD) is proposed. The runoff prediction model is established by combining the success-history adaptive differential evolution algorithm for linear population size reduction (L-SHADE) and simple recurrent unit (SRU). …”
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Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants by Deise Cristina Dal’Ongaro, Cicero Cena, Bruno Spolon Marangoni, Daniele A. Soares-Marangoni

“…This study aimed to explore the development of a method for the diagnosis of congenital syphilis using saliva FTIR spectra and machine learning algorithms in infants aged 0 to 12 months. First, the potential of FTIR for analyzing infant saliva was evaluated. …”
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A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing by Jiayuan Shen, Bing Han, Yang Li, Zongxu Pan, Di Yin, Yugang Feng, Guangzuo Li

“…We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. …”
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Data transmission algorithm for mobile wireless sensor network based on power loss equalization control mechanism by Lijun LI, Fuquan ZHANG, Hongfei LIU

“…In order to solve the problem of synchronization addressing and the inadequacy of power interaction among nodes in the current mobile wireless sensor network,a new data transmission algorithm for mobile wireless sensor network was proposed.Firstly,the broadcast mechanism was adopted to realize synchronous control packet transmission and reduce the pressure caused by the synchronization flow to the addressing process.Then regional node flow valve control mechanism was used,and data traffic between sink nodes and regional node links were recorded and got by interception,flow link equalization was further adopted to promote traffic equalization.in the further step.Finally,the limited bandwidth based on wheel number-sink link jitter screening mode could be identified,and the transmission failure due to limited bandwidth was reduced.Simulation results show that compared with the bandwidth of the root zone node and widely used in limiting transmission algorithm,node link stability encoding algorithm and hierarchical encoding algorithm,the data transmission bandwidth can be improved,the packet loss rate can be reduced,and the practical needs can be better met.…”
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An Integrated Fault Diagnosis Method for Rotating Machinery Based on Improved Multivariate Multiscale Amplitude-Aware Permutation Entropy and Uniform Phase Empirical Mode Decomposi... by Jiancheng Gong, Xiaoqiang Yang, Fan Pan, Wuqiang Liu, Fuming Zhou

“…This algorithm is combined with the Uniform Phase Empirical Mode Decomposition (UPEMD) method and the t-distributed Stochastic Neighbor Embedding (t-SNE) method, forming a new time-frequency multiscale feature extraction method. …”
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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…However, with the increase in fracturing, drilling, and sand-washing operations, the erosion of coiled tubing walls caused by solid particles has become one of the main failure modes. To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. …”
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Validation of three models (Tolcher, Levine, and Burke) for predicting term cesarean section in Chinese population by Fangcan Sun, Minhong Shen, Bing Han, Youguo Chen, Fangfang Wu

“…Univariate analysis was used to screen out the factors that may increase the risk of CS. …”
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