Recent Progress about Flight Delay under Complex Network by Tang Zhixing, Huang Shan, Han Songchen

“…Real flight data may be utilized to validate and revise the detection and prediction models. (3) It is of great importance to explore how to predict flight delay propagations and identify best spreaders at a low cost of calculation complexity. …”
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SynC2S: An Efficient Method for Synthesizing Tabular Data With a Learnable Pre-Processing by Jiwoo Kim, Seri Park, Junsung Koh, Dongha Kim

“…Furthermore, as a by-product, we claim that SynC2S could be a favorable option to solve over-sampling tasks, constructing high-performance prediction models by generating synthetic data for the minority class.…”
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Indirect Estimation of Swelling Pressure of Expansive Soil: GEP versus MEP Modelling by Fazal E. Jalal, Mudassir Iqbal, Mohsin Ali Khan, Babatunde A. Salami, Shahid Ullah, Hayat Khan, Marwa Nabil

“…Also, the proposed predictive models were compared with widely used AI models (ANN, ANFIS, RF, GB-T, DT, and SVM). …”
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Engineering Application of an Identification Method to Shock-Induced Vortex Stability in the Transonic Axial Fan Rotor by Yan Xue, Ning Ge

“…As the additional findings, a universal tip vortex model is established and the characteristics of vortex breakdown or not are also summarized under different load levels. To ensure the prediction accuracy of all numerical methods selected in this research, detailed comparisons are made between computational and experimental results before flow analysis. …”
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Metagenomic investigation of viruses in green sea turtles (Chelonia mydas) by Hongwei Li, Yuan Chen, Zhongrong Xia, Daohua Zhuang, Feng Cong, Yue-Xiao Lian

“…Additionally, most of the viral contigs were not assigned to any known family or genus, implying a large knowledge gap in the taxonomy of green sea turtle gut viruses. Host prediction showed that most viruses were connected to two phyla: Bacteroidetes and Firmicutes. …”
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Understanding integrative approach of translational bioinformatics on cardiovascular disease: Myocardial Ischemia by Yeswanth Ranganathan, Saayaa Nazar, Ravi Shankar Krishnan, Yuvaraj Dinakarkumar, Vijayalakshmi Varadarajan, Lenita Sebastian, Brindha Rethinam

“…Translational bioinformatics bridges the gap between biological discoveries and clinical applications, enabling early disease identification, therapy response confirmation, and prognosis prediction. It facilitates the integration and analysis of vast amounts of clinical data, hence advancing clinical research and enhancing therapeutic approaches. …”
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A New Plant Indicator (Artemisia lavandulaefolia DC.) of Mercury in Soil Developed by Fourier-Transform Near-Infrared Spectroscopy Coupled with Least Squares Support Vector Machine by Lu Xu, Qiong Shi, Bang-Cheng Tang, Shunping Xie

“…The LS-SVM classification model of ALDC samples was established based on the original spectra, smoothed spectra, second-derivative (D2) spectra, and standard normal transformation (SNV) spectra, respectively. The prediction accuracy of D2-LS-SVM was the highest (0.950). …”
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The Seasonal Correlation Between El Niño and Southern Oscillation Events and Sea Surface Temperature Anomalies in the South China Sea from 1958 to 2024 by Jun Song, Lingxiang Yao, Junru Guo, Yanzhao Fu, Yu Cai, Meng Wang

“…Overall, these results enhance our understanding of ENSO’s influence on the South China Sea and provide valuable insights for climate prediction and ecosystem protection in the region.…”
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Surface Multi-Hazard Effects of Underground Coal Mining in Mountainous Regions by Xuwen Tian, Xin Yao, Zhenkai Zhou, Tao Tao

“…Additionally, the subsidence continued even after coal mining operations concluded. Predictions derived from the logistic model indicate that the duration of residual surface subsidence in the study area is approximately 1 to 2 years. …”
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Analyzing Coronary Artery Disease in Patients with Low CAC Scores by 64-Slice MDCT by Nan-Han Lu, Lee-Ren Yeh, Tai-Been Chen, Yung-Hui Huang, Chung-Ming Kuo, Hueisch-Jy Ding

“…This work uses a novel efficient approach to predict CAD in patients with low CAC scores. Materials and Methods. …”
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Improvement of modeling on the Pidgeon process for magnesium production by introducing the variable thermophysical properties by Li R.-B., Wang C., Wang Z., Yang P.-X., Xue F., Liu F.-Q., Zhang S.-J.

“…The improved model can provide a more accurate quantitative prediction for magnesium reduction in the Pidgeon process, which is important for key equipment innovation and the development of new magnesium production techniques.…”
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In silico Analysis of Human Endothelial Cell-specific Molecule 1 and Interleukin-6 Genetic Variants Involved in Coronary Artery Disease by Vineet Kulkarni, Sukanya Shetty, Roopa Bhandary, Yanglem Mary

“…The MUpro and I-Mutant web tools were used to predict protein stability, and the Group-based Prediction System (GPS)-MSP tool was used for posttranslational modification analysis. …”
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Distribution, Size, and Shape of Abdominal Aortic Calcified Deposits and Their Relationship to Mortality in Postmenopausal Women by Melanie Ganz, Marleen de Bruijne, Erik B. Dam, Paola Pettersen, Morten A. Karsdal, Claus Christiansen, Mads Nielsen

“…We analysed inter-/intraobserver reproducibility and predictive ability of mortality after 8-9 years via Cox regression leading to hazard ratios (HRs). …”
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Discovery of Anti-inflammatory Peptides from Channa argus Using Virtual Screening, Molecular Docking, and Cell Model by XIANG Huan, LU Meiming, CHEN Shengjun, HUANG Hui, HU Xiao, ZHAO Yongqiang, WEI Ya

“…Anti-inflammatory peptides were selected by the combined use of physicochemical prediction, molecular docking, and a cell model, and their mechanisms of action were elucidated. …”
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Quality by Design (QbD) Assisted Fabrication of Fast Dissolving Buccal Film for Clonidine Hydrochloride: Exploring the Quality Attributes by Pankaj V. Dangre, Ram D. Phad, Sanjay J. Surana, Shailesh S. Chalikwar

“…., HPMC E15 (X1) and PEG 400 (X2), as independent variables (factors) on thickness (mm) (Y1), disintegration time (s) (Y2), folding endurance (Y3), and tensile strength (kg) (Y4). Furthermore, prediction profiler assists in predicting composition of best formulation encompassing desired targeted response. …”
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Research on Highway Roadside Safety by Guozhu Cheng, Rui Cheng, Yulong Pei, Juan Han

“…This paper reviewed the different prediction methods and evaluation models for the frequency and severity of roadside accidents. …”
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Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation by Xiaoming Zhang, Lean Yu, Hang Yin

“…However, there may be problems with data scarcity, feature redundancy, and poor predictive performance. Additionally, data collected over a long time span may cause differences in the data distribution, and classic supervised learning methods may exhibit poor predictive abilities under such conditions. …”
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New Approach for the Calculation of the Intraocular Lens Power Based on the Fictitious Corneal Refractive Index Estimation by Joaquín Fernández, Manuel Rodríguez-Vallejo, Javier Martínez, Ana Tauste, David P. Piñero

“…To identify the sources of error in predictability beyond the effective lens position and to develop two new thick lens equations. …”
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Assimilation of GNSS Measurements for Estimation of High‐Latitude Convection Processes by Daniel S. Miladinovich, Seebany Datta‐Barua, Aurora López Rubio, Shun‐Rong Zhang, Gary S. Bust

“…Additionally ingesting northward line‐of‐sight neutral wind measurements from a Fabry‐Perot interferometer at Millstone Hill makes little difference in the agreement between zonal ion drift predictions and measurements. Estimation of only electric potential reduces the agreement between the assimilated prediction of the field‐perpendicular zonal drifts and ISR measurements significantly.…”
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Influence of Pilocarpine Eyedrops on the Ocular Biometric Parameters and Intraocular Lens Power Calculation by Ruxin Gao, Jinkun Liu, Xiaojie Zhou, Luping Huang, Weiyi Huang, Yingying Xue, Fei Wang, Songjian Gong, Renyi Wu, Yuhong Wang

“…Lens position (LP) was calculated, and the IOL power prediction based on the ocular biometric parameters was performed using the Barrett Universal II, Haigis, Hoffer Q, Holladay I, or SRK/T formulas before and after pilocarpine application. …”
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