Estimation of translational importance of mammalian mRNA nucleotide sequence characteristics based on ribosome profiling data by O. A. Volkova, Yu. V. Kondrakhin, R. N. Sharipov

“…Now it seems to be possible to reveal translationally important mRNA parameters and predict translation efficiency based on their nucleotide sequences. …”
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Ultrasonographic evaluation of the thorax in dogs with tick paralysis by Erdem Gülersoy, Canberk Balıkçı, İsmail Günal, Adem Şahan, Esma Kısmet

“…Thus, the aim of this study is to describe thoracic ultrasonography lesions in dogs with tick paralysis and to identify potential patterns that could aid in diagnosis and prognosis prediction. The animal material consisted of 58 dogs in total, 10 of which were healthy and 48 of which were suspected to be affected by tick paralysis. …”
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Few-Shot Graph Anomaly Detection via Dual-Level Knowledge Distillation by Xuan Li, Dejie Cheng, Luheng Zhang, Chengfang Zhang, Ziliang Feng

“…In our approach, we initially train a teacher model to generate prediction distributions as soft labels, capturing the entropy of uncertainty in the data. …”
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Diagnostic value of multi-parameter ultrasound evaluation in sepsis complicated by acute kidney injury by Liu Wang, Xiang Wang

“…Additionally, logistic regression analysis was conducted to determine the influencing factors of sepsis complicated with AKI. The prediction value was evaluated using a receiver operating characteristic (ROC) curve.Results In the AKI group, creatinine, CysC, urea, MPUS score, RPT, and RI values were significantly higher, while the 24-h urine volume was lower than those in the non-injury group (p < 0.01). …”
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The role of hybrid models in financial decision-making: Forecasting stock prices with advanced algorithms by Xiaoyi Zhu

“…This approach allowed the model to generalize effectively across a variety of global indices, as demonstrated by its high prediction accuracy (coefficient of determination (R2) values exceeding 0.98 for the Dow Jones, CSI, Nikkei, and DAX indices). …”
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Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma by Mengmeng Hua, Tao Li

“…Abstract To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcinoma (LUAD). LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somatic mutation data from The Cancer Genome Atlas LUAD cohort were analyzed to identify lactylation cancer subtypes (CSs) using 10 multiomics ensemble clustering techniques. …”
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Permeability Enhancement Technology for Soft and Low-Permeability Coal Seams Combined with Hydraulic Perforation and Hydraulic Fracturing by Zhengjie Shang, Zhaofeng Wang, Zhiheng Cheng, Hongbing Wang, Liang Chen, Lei Li, Jianhua Fu, Hao Liu

“…The gas pressure in the No. 21 coal seam decreased from 1.1 MPa to 0.4 MPa, and the gas content decreased from 15.96 m3/t to 5.6 m3/t. All outburst prediction indexes measured on site did not exceed their respective limits. …”
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Dynamic Warping Network for Semantic Video Segmentation by Jiangyun Li, Yikai Zhao, Xingjian He, Xinxin Zhu, Jing Liu

“…Furthermore, we introduce the temporal consistency loss including the feature consistency loss and prediction consistency loss to explicitly supervise the warped features instead of simple feature propagation and fusion, which guarantees the temporal consistency of video segmentation. …”
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Local-Global and Multi-Scale (LG-MS) Mixer Architecture for Long-Term Time Series Forecasting by Zhennan Peng, Boyong Gao, Ziqi Xia, Jie Liu

“…To capture a more comprehensive effective information within the components, we then utilize a customized patch-based triple attention local-global information extractor that models both temporal feature information and variable dependencies, alongside an MLP-based feature interaction iterator facilitating interactions among multi-scale information to guide macro-level predictions. Finally, we integrate the predictions from the multi-scale sequences to leverage their complementary advantages. …”
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A comprehensive metabolome profiling of Terminalia chebula, Terminalia bellerica, and Phyllanthus emblica to explore the medicinal potential of Triphala by Santhosh N. Hegde, Lavanya Devi K, Mahima Choudhary, Nandita Menon, Gurmeet Singh

“…LCMS/MS data analysis was performed on the resultant metabolites, with bioinformatics tools employed for pathway enrichment, target prediction, and classification of identified compounds. …”
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Du mythe de l’efficience des marchés au krach by David Bourghelle, Pauline Hyme

“…This kind of rationality is entirely directed toward the prediction of what the dominant opinion of the market, in the form of the price, will be. …”
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Preparation of Saccharomycopsis fibuligera Fuqu and Its Application in the Production of Xiaoqu Baijiu by LIU Xiao, HUANG Zhiguo, WEI Chunhui, REN Zhiqiang, XIE Jun, DENG Jie

“…In addition, PICRUSt2 functional prediction confirmed that the abundance of enzymes involved in the metabolism of acetic acid and ethyl acetate was higher in the experimental group than in the control group during the fermentation process. …”
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Field Observations during the Eleventh Microwave Water and Energy Balance Experiment (MicroWEX-11): from April 25, 2012, through December 6, 2012 by Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Daniel Preston, Patrick Rush, Tim H.M. van Emmerik, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, Susan Steele-Dunne, Roger De Roo, Ruzbeh Akbar, Ella Baar, Max Wallace, Anthony England

“… This new report from UF/IFAS researchers provides another set of observation data that can be used to develop better models for accurate prediction of weather and near-term climate. It describes the observations conducted during the MicroWEX-11, a season-long experiment incorporating active and passive microwave observations for bare soil, elephant grass, and sweet corn using a variety of sensors to understand land–atmosphere interactions and their effect on observed microwave signatures. …”
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Research on Antenna Propagation Loss Model in Rail Transit Tunnel based on Multi-dimensional Scenario Analysis by ZHAO Yifan, ZOU Jinbai, ZHAO Zhenglian, XU Zhipeng, ZHOU Qing

“…［Objective］ As tunnel is one of the typical environments for rail transit wireless communication, the accurate prediction of radio wave signal strength in tunnels has always attracted wide attention and study. …”
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Physical experimental simulation of unconventional reservoir formation process for carboniferous in Hudson Oilfield, Tarim Basin by Rujun Wang, Yongliang Tang, Wei Zhou, Daiyu Zhou, Zangyuan Wu, Guangqiang Shao

“…And the application of advanced simulations, enhancing unconventional reservoir prediction accuracy by 25% compared to standard geological techniques. …”
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Detection of Corn Quality Based on Surface-Enhanced Raman Spectroscopy and Electronic Nose Technology by HuiHe Yang, XiaoYan Wei, Guifang Wu, PengCheng Qiu, JiaNing Di, XiangPeng Zhao, WenDong Zhong, He Ren

“…The results showed that the model’s coefficient of determination of the test set for predicting AFB1 reached 0.70, and the model’s coefficient of determination of the test set for predicting OTA reached 0.74. …”
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Reliability Estimation of Parameters of Helical Wind Turbine with Vertical Axis by Adela-Eliza Dumitrascu, Badea Lepadatescu, Dorin-Ion Dumitrascu, Anisor Nedelcu, Doina Valentina Ciobanu

“…This can be achieved through a rigorous design, appropriate simulation and testing, and proper construction. The reliability prediction and analysis of these systems will lead to identifying the critical components, increasing the operating time, minimizing failure rate, and minimizing maintenance costs. …”
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Bearing Capacity of Recycled Self-Compacting Concrete-Filled Circular Steel Tubular Long Columns Subjected to Axial Load by Feng Yu, Jie Song, Shuangshuang Bu, Jingfeng Wang, Haiying Wan, Wanyu Shen, Wei Huang, Yuan Fang

“…Based on the combined tangent modulus theory and bearing capacity of the RSCCFCST short columns, two estimation models are presented to predict the ultimate bearing capacity of the RSCCFCST long columns. …”
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Analysis and Simulation of the Early Warning Model for Human Resource Management Risk Based on the BP Neural Network by Xue Yan, Xiangwu Deng, Shouheng Sun

“…Human resource management risks are due to the failure of employer organization to use relevant human resources reasonably and can result in tangible or intangible waste of human resources and even risks; therefore, constructing a practical early warning model of human resource management risk is extremely important for early risk prediction. The back propagation (BP) neural network is an information analysis and processing system formed by using the error back propagation algorithm to simulate the neural function and structure of the human brain, which can handle complex and changeable things that do not have an obvious linear relationship between output results and input factors, so as to find the objective connection between the two. …”
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CRIP1 inhibits cutaneous melanoma progression through TFAM-mediated mitochondrial biogenesis by Jianqiang Wu, Lixia Chen, Peijun Wen

“…However, the biological function and underlying mechanisms of CRIP1 in melanoma progression are largely unknown. Bioinformatic prediction of CRIP1 expression in melanoma and its association with clinical parameters and prognosis of patients. …”
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